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**SiROP is an exclusive network of leading universities in science and technology**
Why join SiROP?
- Hundreds of open positions readily available online
- Direct contact and easy application procedure without any bureaucracy
- Its free and will always be! Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Selection of open positions in our database Selection of open positions in our database modeling such a circuit to simulate the pulse waveform we generate. This investigation could outline the parameters that affect the parameters we are interested in, like peak voltage, pulse rise rate, pulse duration, etc - Electrical Engineering
- Master Thesis
| In a thesis project for Frenetic you would be working on magnetic modeling in the field of power electronics. Projects could include enhancing core loss models using an AI-enhanced database, or improving magnetic component design processes through AI/ML algorithms. - Electrical Engineering
- Master Thesis, Semester Project
| In this master thesis, the student will investigate the strategy for the switching of long primary motor segments, the transient effects caused by it, possible mitigation measures (i.e. filters) and propose a hardware setup for the final configuration. - Electrical Engineering
- Master Thesis
| In this master thesis, the student will investigate different linear motor types and topologies for the future 3km AlphaTube vacuum transport demonstrator, such as the permanent magnet synchronous motor and the synchronous reluctance motor. - Electrical Engineering
- Master Thesis
| xxx - Electrical Engineering
- Semester Project
| In this master thesis, the student will consider the expected power profile of a hyperloop vehicle, and the models relative to the propulsion and levitation systems will be extracted and compared with the corresponding one of high speed railway. After having established the expected performance, the thesis will focus on which power system architecture is most suitable of future Hyperloop systems. - Electrical Engineering
- Master Thesis
| xxx - Electrical Engineering
- Master Thesis, Semester Project
| xxx - Electrical Engineering
- Master Thesis
| xxx - Electrical Engineering
- Master Thesis
| The aim of this master thesis is to propose a design of a DC/DC insulated converter integrated with the PV plant into the 3kV DC bus, taking into account the spatial peculiarities of a 3km long linear PV array. - Electrical Engineering
- Master Thesis
| We are looking for a dynamic and proactive research software engineer to advance the impact of open-source software for musculoskeletal image analysis - Software Engineering
- Internship
| This master’s thesis is dedicated to developing an advanced nutrition tracking system for hospitals, integrating QR-code recognition and structured light camera technology. The focus is to significantly enhance the precision of food volume measurements and patient meal tracking with machine learning, thereby improving nutritional monitoring accuracy. - Computer Vision, Medical and Health Sciences, Software Engineering
- Master Thesis
| Study State-Space Models (SSMs) within the realm of Reinforcement Learning (RL) and ideally apply it in Robotics field. - Computer Vision, Intelligent Robotics, Knowledge Representation and Machine Learning
- Master Thesis
| This project focuses on utilizing various techniques for Video to Events generation. - Computer Vision
- Master Thesis
| In this project, we want to explore possible extensions of predictive control barrier functions to the multi-agent setting. Predictive control barrier functions [1] allow certifying safety of a system in terms of constraint satisfaction and provide stability guarantees with respect to the set of safe states in case of initial feasibility. This allows augmenting any human or learning-based controller with closed-loop guarantees through a so-called safety filter [2] which is agnostic to the primary control objective. As current formulations are restricted to single agents, the goal is to investigate how this formulation can be extended for multi-agent applications and how the interactions between the agents can be exploited in order to reduce computational overhead. - Engineering and Technology, Systems Theory and Control
- Master Thesis
| This project focuses on developing autonomous robots for synchronized performances on water. Equipped with kinetic water fountains, RGB lighting, and ultrasonic mist generators, the robots are designed to execute planned choreographies. The system utilizes robotics control, wireless communication, and positioning technologies to coordinate movements, and payload activation, facilitating complex pattern generation and synchronization. The objective is to advance the application of distributed robotic systems in creating structured and cohesive visual displays on water. - Arts, Engineering and Technology, Information, Computing and Communication Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| To interpret new observations of exoplanets using telescopes, a better understanding of how gases at high pressures and temperatures mix in their atmospheres is required. The goal of this project is to develop more accurate models for mixtures of major gases in planetary atmospheres at extreme conditions and apply them to interpret recent spectra collected for sub-Neptune planets. - Astronomy and Astrophysics, Chemical Thermodynamics and Energetics, Geochemistry
- Master Thesis
| The goal of the project is to assess the feasibility of using commercially available plantar pressure monitoring devices (so called smart insoles) on the diabetic population. Pressure ulcers are a common complication of the diabetic foot, and monitoring plantar pressure continuously is a potential measure of prevention. Diabetic patients are often prescribed personalized footwear (e.g., curved insoles that accommodate any deformity in the feet). This project aims at assessing the potential of the smart insoles available on the market to monitor plantar pressure in diabetic patients with such custom footwear. - Biomedical Engineering, Medical and Health Sciences
- Bachelor Thesis, Semester Project
| The remarkable agility of animals, characterized by their rapid, fluid movements and precise interaction with their environment, serves as an inspiration for advancements in legged robotics. Recent progress in the field has underscored the potential of learning-based methods for robot control. These methods streamline the development process by optimizing control mechanisms directly from sensory inputs to actuator outputs, often employing deep reinforcement learning (RL) algorithms. By training in simulated environments, these algorithms can develop locomotion skills that are subsequently transferred to physical robots. Although this approach has led to significant achievements in achieving robust locomotion, mimicking the wide range of agile capabilities observed in animals remains a significant challenge. Traditionally, manually crafted controllers have succeeded in replicating complex behaviors, but their development is labor-intensive and demands a high level of expertise in each specific skill. Reinforcement learning offers a promising alternative by potentially reducing the manual labor involved in controller development. However, crafting learning objectives that lead to the desired behaviors in robots also requires considerable expertise, specific to each skill.
- Information, Computing and Communication Sciences
- Master Thesis
| Humanoid robots, designed to mimic the structure and behavior of humans, have seen significant advancements in kinematics, dynamics, and control systems. Teleoperation of humanoid robots involves complex control strategies to manage bipedal locomotion, balance, and interaction with environments. Research in this area has focused on developing robots that can perform tasks in environments designed for humans, from simple object manipulation to navigating complex terrains. Reinforcement learning has emerged as a powerful method for enabling robots to learn from interactions with their environment, improving their performance over time without explicit programming for every possible scenario. In the context of humanoid robotics and teleoperation, RL can be used to optimize control policies, adapt to new tasks, and improve the efficiency and safety of human-robot interactions. Key challenges include the high dimensionality of the action space, the need for safe exploration, and the transfer of learned skills across different tasks and environments. Integrating human motion tracking with reinforcement learning on humanoid robots represents a cutting-edge area of research. This approach involves using human motion data as input to train RL models, enabling the robot to learn more natural and human-like movements. The goal is to develop systems that can not only replicate human actions in real-time but also adapt and improve their responses over time through learning. Challenges in this area include ensuring real-time performance, dealing with the variability of human motion, and maintaining stability and safety of the humanoid robot.
- Information, Computing and Communication Sciences
- Master Thesis
| In recent years, advancements in reinforcement learning have achieved remarkable success in teaching robots discrete motor skills. However, this process often involves intricate reward structuring and extensive hyperparameter adjustments for each new skill, making it a time-consuming and complex endeavor. This project proposes the development of a skill generator operating within a continuous latent space. This innovative approach contrasts with the discrete skill learning methods currently prevalent in the field. By leveraging a continuous latent space, the skill generator aims to produce a diverse range of skills without the need for individualized reward designs and hyperparameter configurations for each skill. This method not only simplifies the skill generation process but also promises to enhance the adaptability and efficiency of skill learning in robotics. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| Recent advances in physically simulated humanoids have broadened their application spectrum, including animation, gaming, augmented and virtual reality (AR/VR), and robotics, showcasing significant enhancements in both performance and practicality. With the advent of motion capture (MoCap) technology and reinforcement learning (RL) techniques, these simulated humanoids are capable of replicating extensive human motion datasets, executing complex animations, and following intricate motion patterns using minimal sensor input. Nevertheless, generating such detailed and naturalistic motions requires meticulous motion data curation and the development of new physics-based policies from the ground up—a process that is not only labor-intensive but also fraught with challenges related to reward system design, dataset curation, and the learning algorithm, which can result in unnatural motions.
To circumvent these challenges, researchers have explored the use of latent spaces or skill embeddings derived from pre-trained motion controllers, facilitating their application in hierarchical RL frameworks. This method involves training a low-level policy to generate a representation space from tasks like motion imitation or adversarial learning, which a high-level policy can then navigate to produce latent codes that represent specific motor actions. This approach promotes the reuse of learned motor skills and efficient action space sampling. However, the effectiveness of this strategy is often limited by the scope of the latent space, which is traditionally based on specialized and relatively narrow motion datasets, thus limiting the range of achievable behaviors.
An alternative strategy involves employing a low-level controller as a motion imitator, using full-body kinematic motions as high-level control signals. This method is particularly prevalent in motion tracking applications, where supervised learning techniques are applied to paired input data, such as video and kinematic data. For generative tasks without paired data, RL becomes necessary, although kinematic motion presents challenges as a sampling space due to its high dimensionality and the absence of physical constraints. This necessitates the use of kinematic motion latent spaces for generative tasks and highlights the limitations of using purely kinematic signals for tasks requiring interaction with the environment or other agents, where understanding of interaction dynamics is crucial.
We would like to extend the idea of creating a low-level controller as a motion imitator to full-body motions from real-time expressive kinematic targets. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| The Advanced Manufacturing Lab (am|z) is excited to announce a thesis opportunity focusing on the development of a highly parallelizable modeling framework for additive manufacturing (AM) processes, particularly laser powder bed fusion (LPBF). Our research primarily delves into advancing manufacturing techniques, with a special emphasis on additive manufacturing. We have developed a robust numerical simulation framework called iMFREE utilizing Smoothed Particle Hydrodynamics (SPH) for multi-physics applications like LPBF. However, there is a need to enhance computational efficiency, specifically through parallelization via Message Passing Interface (MPI). This project offers an excellent chance for students to deepen their knowledge in parallel computation while working hands-on with a mature computational framework. - Engineering and Technology, Information, Computing and Communication Sciences
- ETH Zurich (ETHZ), Master Thesis
| In the burgeoning field of deep reinforcement learning (RL), agents autonomously develop complex behaviors through a process of trial and error. Yet, the application of RL across various domains faces notable hurdles, particularly in devising appropriate reward functions. Traditional approaches often resort to sparse rewards for simplicity, though these prove inadequate for training efficient agents. Consequently, real-world applications may necessitate elaborate setups, such as employing accelerometers for door interaction detection, thermal imaging for action recognition, or motion capture systems for precise object tracking. Despite these advanced solutions, crafting an ideal reward function remains challenging due to the propensity of RL algorithms to exploit the reward system in unforeseen ways. Agents might fulfill objectives in unexpected manners, highlighting the complexity of encoding desired behaviors, like adherence to social norms, into a reward function.
An alternative strategy, imitation learning, circumvents the intricacies of reward engineering by having the agent learn through the emulation of expert behavior. However, acquiring a sufficient number of high-quality demonstrations for this purpose is often impractically costly. Humans, in contrast, learn with remarkable autonomy, benefiting from intermittent guidance from educators who provide tailored feedback based on the learner's progress. This interactive learning model holds promise for artificial agents, offering a customized learning trajectory that mitigates reward exploitation without extensive reward function engineering. The challenge lies in ensuring the feedback process is both manageable for humans and rich enough to be effective. Despite its potential, the implementation of human-in-the-loop (HiL) RL remains limited in practice. Our research endeavors to significantly lessen the human labor involved in HiL learning, leveraging both unsupervised pre-training and preference-based learning to enhance agent development with minimal human intervention. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| Knee kinematics is critical for diagnosing pathologies such as osteoarthritis and providing guidance for implant design. Estimating knee kinematics requires aligning a model with a target X-ray image. This estimation process, often implemented by human labor, can be very time-consuming. This research aims to use a deep learning network to estimate the pose (kinematics) from X-ray images, partially replacing manual labor. Such a network should predict a pose from a current fluoroscopic image. By the end of this project, a robust pipeline should be completed, achieving baseline performance to provide convincing pose estimation for images from different modalities (single-plane system & dual-plane system; natural bone model & implant model). - Biomechanics, Biomedical Engineering, Computer Vision
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Fully Funded PhD Scholarship (Fall 2024/Spring 2025) at Nanyang Technological University, Singapore: AI for Drug Discovery and Multi-Modal Large Language Models in Medicine - Artificial Intelligence and Signal and Image Processing, Computational Biology and Bioinformatics
- PhD Placement
| Scanning ion conductance microscopy (SICM) is the non-contact SPM technology to image live cells based on glass capillaries with a nanometric aperture. It applies a voltage and measures the ionic current flowing through the pipette above the sample in the buffer solution: the recorded current represents the feedback signal to measure the topography of the sample. In collaboration with Prof. Fantner at EPFL, this project aims to assemble a state of the art high-speed SICM to enable time-resolved live cell imaging. - Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Nanotechnology, Signal Processing
- Bachelor Thesis, Course Project, ETH Zurich (ETHZ), Lab Practice, Master Thesis, Summer School
| What about implantable self-powering devices to monitor biophysical signals at nanoscale? As a part of the interdisciplinary frontier between material science and new biomedical applications, being able to monitor biological or physical markers and signals, allows for a better treatment from both the diagnostic and healing point of view. Among them, biocompatible and non-intrusive wearable monitoring devices, which are so flexible to adhere perfectly to biological tissue, and even to cells like neurons, gain increasing interest. However, fabricating the devices and the electrodes at nano/microscale remains a challenge.
FluidFM is a force-controlled nanopipette, a versatile tool also for 2D patterning and 3D printing in liquid environment, opening the opportunity to manufacture the devices at the sub-micron scale.
We are going to create the devices and electrodes depositing conductive polymers with the FluidFM and then to perform the opportune electrical characterization. - Electrical and Electronic Engineering, Materials Engineering, Medical and Health Sciences, Physics
- Master Thesis
| The aim of the project is to investigate the benefits, requirements and drawbacks of physics informed neural networks in the context of personalised cardiac and cardiovascular models - Biomechanical Engineering, Clinical Engineering, Computation Theory and Mathematics, Fluidization and Fluid Mechanics, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Simulation and Modelling
- Master Thesis
| Pemphigus vulgaris (PV) is a unique group of autoimmune diseases. Researches have demonstrated that antibody-induced disruption of Dsg3 transadhesion initiates a signaling response in basal keratinocytes followed by loss of tissue integrity. The complexity of morphogenesis and tissue regeneration implies the existence of a transcellular communication network in which individual cells sense the environment and coordinate their biological activity in time and space.
To understand the fascinating ability of tissue self-organization, comprehensive study of biophysical properties (cell topography and bioelectricity) in combination with the analysis of biochemical networks (signaling pathways and genetic circuits) is required.
Together with the University of Bern and University of Lübeck, we aim to utilize the tools to study the topography and electrophysiology (cell potential, ion channel recording, localized ion detection, charges) of HPEK cells (human primary keratinocytes cells) to unravel the signaling pathways of the disease. We utilize optical imaging (fluorescence dyes) and biosensing tools (including the state of the art hs-SICM and electrical FluidFM setup) to study HPEK cells upon desmosome disruption.
- Biology, Biomedical Engineering, Chemistry, Electrical and Electronic Engineering, Interdisciplinary Engineering, Medical and Health Sciences
- Bachelor Thesis, Lab Practice, Master Thesis, Semester Project, Summer School
| The project focuses exploiting generative AI to build synthetic numerical phantom for cardiac anatomy and function suitable for representing population variability. - Biomechanical Engineering, Information, Computing and Communication Sciences
- Master Thesis
| A Master thesis position is available with a flexible start date and duration, preferentially of > 6 months in the Institute of Neuropathology, led by Professor Adriano Aguzzi. - Genetic Engineering and Enzyme Technology, Neurogenetics
- Master Thesis
| The goal of the project is to develop and test a smart sock prototype for plantar pressure measurements. Existing previously developed textile pressure sensors are to be integrated in a standard sock. This technology can be used for plantar pressure monitoring in diverse wearable applications ranging from healthcare to sports. - Biomedical Engineering, Medical and Health Sciences
- Master Thesis
| Spinal deformities are omnipresent and difficult to assess and monitor accurately. One of the most prevalent spinal deformities in children and adolescents is scoliosis, a three-dimensional deformation of the spine. To date, the standard approach for assessing and monitoring scoliosis is biplanar radiography using ionizing radiation. Thermal imaging has been investigated as a non-invasive adjunctive assessment method, as the scoliotic back shows a typical thermal asymmetry between contralateral sides. In this project, the usefulness and accuracy of thermal imaging in the context of spine assessment will be investigated and evaluated. - Biomechanics, Biomedical Engineering
- ETH Zurich (ETHZ), Internship, Master Thesis
| The study of small-molecule supramolecular hydrogelators (SMSHs) is of great interest, both fundamental and applicative. Their self-assembly most often leads to the formation of fibrillar structure and can be used as a model for the fibrillation of biologically-relevant entities, also their ability to form gels with tunable mechanical properties suggest many promising materials-related applications. In this context, aminoacid-based SMSHs (AA-SMSHs) have a special relevance because of opportunities offered e.g. in terms of biocompatibility and biomimetics, as well as in terms of variety of molecular design possibilities. Usually, the sol-gel behavior of AA-SMSHs is pH-dependent thanks to the presence of one or more pH-responsive groups, especially carboxylic acid –COOH ones. For these reasons, pH-responsive SMSHs (aminoacid-based and non) have been and still are the subject of intense investigation. Nevertheless, their behavior is far from being completely understood. - Biological and Medical Chemistry, Biomaterials, Materials Engineering, Physical Chemistry of Macromolecules, Supramolecular Chemistry
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| In this project, you will have the opportunity to contribute to the development and optimization of a single-molecule sensor designed for the detection, identification, and sequencing of important biomolecules such as DNA and proteins. The sensor technology is built upon the principles of microfluidics, nanofabrication, and machine-learning data analysis. It is an excellent fit for students who possess skills and a strong interest in these fields and are eager to engage in an interdisciplinary project with significant potential impact. - Biology, Chemistry, Engineering and Technology, Medical and Health Sciences, Physics
- Master Thesis
| Combine two exploding fields in computer science: machine learning and agent-based modelling.
Based on preclinical and in vitro studies of cell behaviour and cytokine reaction-diffusion and mechanical tests we have generated an in-house biofidelic agent-based model of the human skeleton and its response to diseases and their treatments. This model reproduces the effects of several widely used osteoporosis treatments on key parameters used to quantify fracture risk. This rule-based approach involves studying bone mechanobiology at the cell scale and extrapolating this to millions of cells at the tissue scale to understand the pharmacokinetics of treatments and identify possible new therapies and approaches to patient-specific treatment.
An alternative approach to in silico prediction of response to treatment is a supervised learning approach where we simply input baseline and follow-up bone scans to a CNN with twelve layers constructed using keras. We then attempt to dive into the black box and quantify what characteristics of the input govern the response of our model. The issue is the clinical data is not big enough to do this well so we use the agent-based model as input to the ML approach to construct a proxy model! This also helps us understand, validate and quantify the uncertainty in the agent-based model. To decide which runs of the agent-based model to use as input to the ML approach to construct the proxy model we use polynomial chaos expansion. - Animal Physiology-Cell, Artificial Intelligence and Signal and Image Processing, Cell Development (incl. Cell Division and Apoptosis), Cellular Interactions (incl. Adhesion, Matrix, Cell Wall), Computation Theory and Mathematics, Modeling and Simulation, Protein Targeting and Signal Transduction
- Bachelor Thesis, Master Thesis, Semester Project
| Problem:
Accurately estimating the weight of food items is a significant challenge in healthcare applications. While state-of-the-art 3D cameras can precisely measure food volume, the lack of datasets with labeled food densities remains a major obstacle for accurately determining food amounts.
Goal of the thesis:
The thesis aims to create a dataset that includes the volume, weight, and 3D scans of various food items using a state-of-the-art structured light camera. Due to the vast variety of foods, compiling a comprehensive dataset is impractical. Therefore, the project will also include training and testing a machine learning model to predict the densities of food items that were not seen during its training.
- Food Engineering, Food Processing, Health Information Systems (incl. Surveillance), Nutrition and Physiology
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| We are searching for an intern to work on the detection of infectious diseases and antimicrobial resistance in wastewater. We are a research and surveillance laboratory that uses state-of-the-art methods on culture- and molecular-based detection of pathogens in complex matrices. We are looking for interns to help us with our surveillance of wastewater for respiratory pathogens including influenza, respiratory syncytial virus, and coronaviruses, as well as surveillance of antimicrobial resistance include MRSA and VRE. Interns are trained on methods for the molecular detection using digital PCR, an advanced tool for quantitative detection of nucleic acids, as well as on extraction of DNA and RNA. Interns are also engaged in the development of new assays, and contribute to management and logistics aspects of the work. All of our methods are directly relevant to commonly used tools in research and clinics for routine diagnostics. - Environmental Sciences, Microbiology
- Internship, Master Thesis
| This moonshot project focuses on researching and exploring the potential of flexible and printable electronics, fabrication technologies, and applications in wearables based on the Voltera NOVA printer. Tasks will include ECAD and MCAD design, manufacturing, and prototype testing. - Electrical and Electronic Engineering, Printing Technology
- Bachelor Thesis, Biomedical (PBL), Energy Harvesting (PBL), Master Thesis, PCB Design (PBL), Semester Project, Wearables (PBL)
| Extend the recent Marigold in different aspects - Computer Vision
- Master Thesis
| This project focuses on designing testbeds for self-sustainable IoT sensors, specifically targeting solar and thermal energy harvesting. Tasks will include ECAD and MCAD design, firmware development, and prototype testing. - Electrical and Electronic Engineering, Mechanical Engineering
- Bachelor Thesis, Energy Harvesting (PBL), Firmware (PBL), Master Thesis, Microcontroller (PBL), PCB Design (PBL), Semester Project, Software (PBL)
| Digital tools, including smartphone apps and conversational agents, hold great promise for enhancing cancer supportive care. These apps can measure patients' symptoms, offering personalized advice on supportive care interventions (e.g., physiotherapy, psychologist, nutritionist) and improving access to such services for cancer patients. Despite the effectiveness of digital health interventions, there is currently a gap in automatic conversational agents that assess symptoms and provide advice on supportive care treatment for cancer patients. This project aims to evaluate the potential of Large Language Models in creating a conversational agent capable of assessing symptoms in cancer patients and offering personalized advice on cancer supportive care. - Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Medical and Health Sciences
- Lab Practice, Master Thesis, Semester Project
| Digital tools, such as smartphone apps, offer promising opportunities to enhance cancer supportive care. Smartphone apps can measure patients' symptoms and provide personalized advice on supportive care interventions. However, to date, a patient-centric approach (i.e., co-designing an app with users) is lacking in the development of such apps. By co-designing the app with users, potential barriers to implementation, such as engagement and usability, can be addressed, leading to increased adherence and a more sucessful implementation. The aim of this project is to use a patient-centric approach to design and develop a smartphone app for cancer patients. - Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
- Lab Practice, Master Thesis, Semester Project
| Are you fascinated by the untapped potential of wearables and smartphone apps in revolutionising the way we manage and treat chronic conditions? This project offers an unparalleled opportunity to dive deep into the world of digital health, exploring how mobile technologies can enhance remote assessment and deliver impactful interventions for conditions ranging from mental health to heart disease, and beyond. - Behavioural and Cognitive Sciences, Medical and Health Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| In this project, we aim to develop a visualization tool designed for rendering and interacting with 3D human motion and scenes. - Computer Graphics, Computer Software, Computer Vision, Engineering and Technology, Virtual Reality and Related Simulation
- Bachelor Thesis, Semester Project
| This project aims to develop advanced
earthquake forecasting models using
bio-inspired Spiking Neural Networks (SNNs).
By exploiting the inherent flexibility of SNNs,
the project will create sparse, multi-step
forecasting models capable of integrating
data from various sources. These models will
be built and tested using the NEST neural
simulator, emphasizing neuroplasticity,
neuromodulation, and neural Darwinism
principles. The goal is to enhance the
efficiency of earthquake predictions by
learning more effectively from limited and
lower-quality data, potentially leading to
significant improvements in forecasting
methods and ultimately reducing the risks
associated with seismic events. - Earthquake Seismology, Knowledge Representation and Machine Learning, Neural Networks, Genetic Alogrithms and Fuzzy Logic
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| Are you interested in designing novel hydrogel materials? We have a project available that focuses on formulating high-performance hydrogels for load-bearing applications. - Chemistry, Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| Cartilage damage in the knee joint can be caused by aging or repetitive actions. It can be treated by surgically removing the damaged cartilage tissue and filling the generated defect with a precisely shaped, healthy cartilage graft. Removing the defected cartilage is commonly done with surgical curettes. We are investigating the use of laser ablation for a more precise defect preparation process. With two different lasers, we managed to obain promising results regarding cell viability in live samples. However, laser parameters such as pulse frequency and energy need to be optimized towards higher cutting efficiency. Your task will be to prepare a setup to test, optimize, and validate various parameter sets using different lasers for articular cartilage ablation. - Biomedical Engineering, Optical Physics
- Master Thesis
| Rare genetic disorders are defined by a prevalence of fewer than 1/2000 people, are chronic and affect patients throughout their lifespan. Osteogenesis imperfecta (OI) is a heterogeneous group of rare genetic bone disorders. OI is a debilitating condition that involves impaired mobility, high fracture incidence and subsequent limb deformities. No treatment exists today that targets the underlying abnormal collagen structure and organization. The mainstay in pediatric care of OI remains antiresorptive therapy with bisphosphonates, despite concerns of long-term effects on depressed bone turnover. While antiresorptive monoclonal antibody treatments are currently undergoing clinical trials in children and young adults, anabolic treatments that directly increase bone formation are currently approved for adults only and decrease in efficacy over a relatively short time span. The experience with these drugs in OI therapy is limited, as clinical studies are still ongoing.
- Biomedical Engineering, Mechanical and Industrial Engineering
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| gpuFlightmare: High-Performance GPU-Based Physics Simulation and Image Rendering for Flying Robots - Engineering and Technology
- Master Thesis, Semester Project
| We aim to explore a range of cognitive impairments associated with various psychiatric and metabolic disorders in mice. Our goal is to identify the critical neural pathway connecting the hypothalamus to subcortical areas, which plays a key role in certain cognitive deficits. This project seeks not only to deepen our comprehension of the brain's intricate operations but also to lay the groundwork for precise therapeutic approaches. We will employ advanced technologies, including optogenetics, fiber photometry, and behavioral assessments, to achieve these objectives.
- Computational Structural Biology, Neurosciences
- Master Thesis
| Reinforcement learning (RL) has demonstrated remarkable success in solving complex control
tasks, such as robotic manipulation and autonomous driving. However, many real-world control
scenarios impose safety constraints that vanilla RL algorithms struggle to satisfy. Guaranteeing
constraint satisfaction in RL is an active field of research. Most safeguarding approaches, such
as predictive safety filters, rely on a (potentially simplified) analytical model of the system under
control. However, this model is treated as a black box from the perspective of the RL agent.
The central idea of this thesis is to incorporate the model knowledge used in safeguarding
into the training process. By using a differentiable simulation as well as a fully differentiable
safeguarding approach, we can obtain the gradient of the reward w.r.t. the agent’s actions. This
promises to improve sample efficiency and speed up training, which is advantageous since
the safeguarding is computationally expensive. We aim to combine previous work on policy
learning with fully differentiable simulation with a differentiable action projection safety shield
that can be integrated into the RL agent’s policy. Your goal is to evaluate whether this approach
can improve sample efficiency and wall clock time during training compared to model-free RL
algorithms with non-differentiable safety layers. - Artificial Intelligence and Signal and Image Processing
- Master Thesis
| Fly like a bird - Engineering and Technology
- Master Thesis, Semester Project
| Visual Representation Learning for Efficient Deep Reinforcement Learning
- Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Despite the growing amount of work on applying causal discovery method with expert knowledge to areas of interest, few of them inspect the uncertainty of expert knowledge (what if the expert goes wrong?). This is highly important since that in scientific fields, causal discovery with expert knowledge should be cautious and an approach taking expert uncertainty into account will be more robust to potential bias induced by individuals. Therefore, we aim to develop an iterative causal discovery method with experts in the loop to enable continual interaction and calibration between experts and data.
Based on the qualifications of the candidates, we can arrange a subsidy/allowance for covering traveling or living costs. - Expert Systems, Health Information Systems (incl. Surveillance), Statistics
- Internship, Master Thesis, Semester Project
| The goal of this project is to implement an 6DoF object pose estimation method that utilizes the embedded sensors of head-mounted devices like the Microsoft HoloLens to improve the accuracy of the 6DoF pose estimation. The proposed method will be thoroughly evaluated and compared against single-view, stereo, and multi-view baselines. - Computer Vision
- ETH Zurich (ETHZ), Master Thesis
| Rapid glacier retreat due to ongoing climate change has a number of impacts, including the destabilization of adjacent mountain slopes. This thesis will analyze seismic data collected at a paraglacial landslide and disentangle various signals due to earthquake activity, iceberg calving events, and rockfall. | The premise Python library is a comprehensive tool designed for the integration and analysis of emerging tech-nologies (e.g., battery electric vehicles, synthetic fuels) using “futurized” life-cycle inventories (LCIs). The library is now used by hundreds of researchers. As part of our commitment to accuracy, transparency, and usability, we are seeking a Master's student with a passion for sustainability, environmental science, or a related field, to assist in the enhancement of our documentation, the refinement of life-cycle inventory descriptions, and the rig-orous quality assurance of our datasets. This internship presents an opportunity to contribute to a vital resource used by researchers and professionals worldwide to make informed decisions on sustainability - Engineering and Technology
- Internship
| This project endeavors to explore the dynamic interplay among calcium ions, bone graft substitutes, and resident immune cells in both orthotopic and ectopic environments, employing advanced ratiometric imaging techniques. - Biomaterials, Cellular Interactions (incl. Adhesion, Matrix, Cell Wall)
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| Complex congenital disorders often result in speech and motor skill impairments, posing communication challenges. Existing non-English speech recognition tools struggle with non-standard speech patterns, compounded by a lack of large training datasets. This project aims to create a personalized framework for training German speech recognition models, catering to the unique needs of individuals with congenital disorders. You will learn to collect data and apply machine learning or deep learning models. - Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| Calibration and software development of an underwater camera-system, designed to observe small river organisms in flow. The goal is to optimize the image processing pipeline and extend the uninterrupted deployment time from 1.5 hrs to a minimum 5 days. Deployments in a river are possible to test the system and developed software improvements. - Environmental Technologies, Freshwater Ecology, Software Engineering
- Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis
| Visual Inertial Odometry (VIO) describes the process of determining the movement trajectory of a mobile agent (e.g. drone, car, VR headset) from image data recorded by a camera combined with inertial measurements from an IMU. It has been shown that the VIO estimation benefits from additional event camera data. The goal of this project is to implement a fast and energy-efficient fusion strategy for event data and classical camera data on either an FPGA or a System on Chip (GAP 9). - Digital Systems, Electrical and Electronic Engineering
- Computer Vision (PBL), Drones (PBL), FPGA (PBL), Master Thesis, Microcontroller (PBL), Neuromorphic (PBL), Semester Project, Software (PBL)
| We are currently looking for Master students in the field of Bioinformatics or Computational Biology for the analysis of cell-free DNA sequencing data. We have several topics which students can apply for depending on their previous expertise and proposed duration of the project (3 months or longer). - Medical Biochemistry: Nucleic Acids, Sequencing and Genomics
- Internship, Lab Practice, Master Thesis, Semester Project
| What optimizations are necessary to make reflective PPG sensors reliably work on tissue with limited blood perfusion?
Note: Candidates should have experience in hardware design (analog circuits, embedded systems, and basic signal processing). - Electrical and Electronic Engineering, Information, Computing and Communication Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| Ingestable and implantable robots that can reside in the human body for long term are revolutionizing the future of personalized medicine. However, one of the most significant challenges facing the widespread adoption of these devices is ensuring a reliable and sustainable power source.Traditional power sources, such as batteries, are impractical for long-term use within these robots due to size constraints, limited energy capacity, and the need for repeated invasive procedures for replacement.
In the Traverso Lab at Brigham and Women’s Hospital (Harvard Medical School), We are exploring advanced engineering approaches to develop novel wireless power transfer (WPT) systems as sustainable powering sources.
- Biomedical Engineering
- Internship, Master Thesis
| In recent years, using deep Reinforcement Learning (RL) for robotic motion policies has demonstrated impressive performance, yielding unprecedented robustness on real hardware. Current sim2real approaches rely on large-scale pre-training with domain randomization to make policies robust but struggle with high-dimensional spaces. Current RL methods are primarily limited by their low sample efficiency. Leveraging differentiable simulators for first-order gradient information shows great results for enhancing sample efficiency. Although promising simulation results exist, deployment on hardware is not usually done. The goal of this thesis is to train quadrupedal locomotion policies in a differentiable simulation framework, and then enable real-world deployment by modifying the simulation, the policy training, or the learning algorithm. Ideally, we can leverage properties of differentiable simulators in this process to improve sim2real transfer by fitting real data. - Intelligent Robotics, Robotics and Mechatronics
- Master Thesis, Semester Project
| The project aims to modernize and improve the process of medical image registration, currently performed through a method known as pTV. Offering a unique combination of numerical programming and practical software implementation, this project promises visibility and application in the ever-evolving field of medical imaging technology. Suitable as a semester-long or master's project. - Computer Software, Medical and Health Sciences
- Bachelor Thesis, Course Project, ETH Zurich (ETHZ), Lab Practice, Master Thesis, Semester Project
| Our goal is to establish a heterocellular 3D printed bone organoid model comprising all major bone cell types (osteoblasts, osteocytes, osteoclasts) to recapitulate bone remodeling units in an in vitro system. The organoids will be produced with the human cells, as they could represent human pathophysiology better than animal models, and eventually could replace them. These in vitro models could be used in the advancement of next-generation personalised treatment strategies. Our tools are different kinds of 3D bioprinting platforms, bio-ink formulations, hydrogels, mol-bioassays, and time-lapsed image processing of micro-CT scans. - Biomaterials, Biomechanical Engineering, Cell Development (incl. Cell Division and Apoptosis), Cellular Interactions (incl. Adhesion, Matrix, Cell Wall), Polymers
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| You will optimize a model of a superconducting radio-frequency accelerator for single electrons, with the goal of achieving the best possible temporal and spatial coherence. To this aim, you will use a code that allows to track the electron through the accelerating cavity and calculate the beam parameters. Since this tracking is time-consuming, you will use surrogate modeling and optimization algorithms. You will work with a diverse team of scientists, engineers and technicians in the electron beam instrumentation group. - Engineering and Technology, Information, Computing and Communication Sciences, Physics
- Internship
| Join us for the project "In SEA2 SpineBot for Safe Intraoperative Intervertebral Stiffness Assessment". - Biomechanical Engineering, Mechanical Engineering, Medical and Health Sciences
- PhD Placement
| Parkinson's disease is a prevalent neurodegenerative condition in individuals over 60 years old. It results from impaired dopaminergic cells in the basal ganglia, leading to gait disturbances and reduced independence. While treatment options like dopamine replacement therapies and Deep-Brain Stimulation (DBS) exist, not all patients benefit from DBS. The lack of reliable biomarkers hampers understanding of surgical outcomes. A new DBS device enables wireless recording of subcortical brain activity, offering novel insights into Parkinson's subcortical activity. To explore personalized therapies, this study will measure the gait performance, neuro-activities like deep brain activity as well as electroencephalography (EEG) during walking in Parkinson's patients. Combining cortical (EEG) and subcortical (DBS) recordings aim to investigate comprehensive brain activity during pathological gait. - Information, Computing and Communication Sciences, Medical and Health Sciences
- Collaboration, Internship, Lab Practice, Master Thesis, Semester Project
| The International Research Center on Water and Environment (CIRSEE) of SUEZ, multinational corporation specializing in water and waste management services, in collaboration with Eawag, the Swiss Federal Institute of Aquatic Science and Technology, offers an internship in the development of an innovative pollution measurement system. - Applied Hydrology (Drainage, Flooding, Irrigation, Quality, etc.), Environmental Sciences
- Internship, Master Thesis
| Fracture healing is a complex process that involves inflammation, angiogenesis, and bone remodeling. The remodelling process helps maintain bone density, repair micro-damage that occurs due to everyday activities, and adapt bones to the specific needs of an individual's body. Mechanical loading is a crucial factor in the regulation of fracture healing. The forces and strains experienced by the bone during everyday activities influence the cellular responses, callus formation, bone deposition, remodelling, and, ultimately, the successful recovery of the fractured bone. The mechanisms underlying spatial cell reorganization during loading, which contributes to fracture healing, remain unclear. The project aims to investigate and explore the fracture healing process of mice using spatial transcriptome changes in response to mechanical loading. By shedding light on this aspect, the project aims to contribute to the broader understanding of fracture healing and potentially pave the way for more effective treatment strategies in the future. - Biological Mathematics, Computational Biology and Bioinformatics, Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences, Physics
- Bachelor Thesis, Course Project, ETH for Development (ETH4D) (ETHZ), ETH Zurich (ETHZ), IDEA League Student Grant (IDL), Internship, Master Thesis, Semester Project
| Do you want to be part of an innovative research project that has the potential to make a real-world impact? If so, then we have an exciting opportunity for you. You will work in a multidisciplinary research environment, and you will have the chance to gain valuable experience in machine learning and data analysis. - Artificial Intelligence and Signal and Image Processing, Environmental Sciences
- Bachelor Thesis, Master Thesis
| Hydroponics is a technique to grow plants without soil, but therefore in nutrient rich solutions. This project aims to construct a small scale fully automated hydroponics system, including the hardware, controller and filter designs, and software implementation. The implementation will finally be validated by growing actual plants. Hydroponics offers an alternative to conventional agriculture, minimizing water usage, fertilization and space requirements and allowing to create optimal environments for plants to grow. Combined it offers a potential future technology to fight food limitations in the face of a rising world population and climate change. - Control Engineering, Electrical Engineering, Systems Theory and Control
- Master Thesis
| Aquaculture is an important global contributor to the production of seafood for human consumption. Currently the industry is phasing several challenges which demand adaptation of novel technologies and methods to move the production from manual and experience-based to more objective approaches [1]. There is need for objective monitoring and inspection of fish conditions to contribute to better fish health and secure fish welfare. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Geothermal energy will be one of the most important assets to solve the world’s energy problems in the future. High Speed Rock Drilling (HSRD), a Swiss company, has been developing and testing an efficient process for deep drilling down to 10 km. - Mechanical and Industrial Engineering
- Master Thesis
| The fish farming industry has seen a rapid growth over the last decades and is today a key provider of seafood [1]. The properties of seawater put limitations on sensor systems that can be used for underwater navigation. Moreover, additional challenges related to robust localization and mapping are imposed by the fish farm environment that must be accounted for when utilizing Unmanned Underwater Vehicles (UUVs) [2]. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| When controlling a system we typically aim to make the system carry out specific tasks, like remaining in a set of states, or reaching a set of states, or both. Recent advances allow to formulate controllers using dynamic programming that trade off such specifications optimally against costs, such as energy consumption. However, these methods rely on full model knowledge; it is the aim of this project to explore model-free attempts towards achieving these objectives. The approach will be validated on the Ball-on-a-Plate system, which is a mechanically actuated plate with a ball on it. - Control Engineering, Systems Theory and Control
- Master Thesis
| Unmanned underwater vehicles (UUVs) have become indispensable tools for inspection, maintenance, and repair (IMR) operations in the underwater domain. Path planning and collision avoidance are fundamental concepts for enabling autonomy for mobile robots. This remains a challenge, particularly for underwater vehicles operating in complex and dynamically changing environments such as fish farms [1]. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Use of robotics such as Unmanned Underwater Vehicles (UUVs) has become essential for several fish farming companies to address current challenges [1]. In particular, Remotely Operated Vehicles (ROVs) have been used for several monitoring operations such as inspection of nets and mooring lines, as well as monitoring and inspection of water quality, the cage environment and fish population. A first step towards autonomous control of robot actions under such conditions is therefore to establish more realistic models and simulation environment of the dynamic cage environment that predict and incorporate structural deformations and the impacts from the surrounding environment, and interactions between these [2]. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| The project aims at investigating material-induced osteoinduction using the available mouse model of orthotopic or ectopic bone graft substitute application. Through the 3D-3D registration of ex vivo and in vivo multiscale micro-CT images, crucial 3D mineralization of the BGS can be investigated. - Biomedical Engineering, Medical and Health Sciences
- Bachelor Thesis, Semester Project
| Fish Farming industry is facing several challenges, with one of the major challenges being related to objective inspection of fish cages to detect irregularities such as holes, biofouling condition [1]. Earlier studies showed that 41% of the escapees from fish farms in Norway are caused by holes in fish cages [2] and the biofouling prevention is crucial to preserve good conditions for the fish growth [1]. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Understanding the distribution and mechanics of velocity and pressure within microaneurysms is crucial for controlling microrobots navigating through them. Traditional methods for velocity and pressure measurement in microchannels, such as particle image velocimetry (PIV) and numerical simulations based on fluidic physics laws, suffer from high computational demands and inability to operate in real-time. Moreover, pure image methods struggle with near-wall regions lacking visible particles. Leveraging recent advancements in machine learning, particularly convolutional neural networks (CNNs), this project proposes a novel approach - a physics-informed CNN integrated with Navier-Stokes equations and optical flow equations. This CNN aims to accurately predict velocity and pressure profiles in microchannel flows in real-time using only flow images and essential physical parameters. The network architecture comprises an encoder-decoder structure with seven convolutional layers, incorporating down-sampling and up-sampling layers. The final output layer produces three channels representing horizontal velocity, vertical velocity, and pressure. Additionally, a physics-informed loss function, incorporating dimensionless Navier-Stokes equation residuals and optical flow equation residuals, enhances the model's performance by integrating knowledge of fluid dynamics and computer vision. This approach represents a promising advancement towards achieving real-time, high-accuracy prediction of velocity and pressure fields in microchannel flows, with potential applications in microrobotics and microfluidics. - Computer Vision, Engineering and Technology, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Physics
- Bachelor Thesis, Master Thesis, Semester Project
| Following trauma or due to degeneration it can be necessary to replace one or more intervertebral discs with an implant, a so-called Total Disc Replacement (TDR). Such devices enable motion though surfaces articulating against each other. While this treatment is clinically successful, it is connected to considerable complication and reoperation rates. Therefore, we are optimizing the design of such an implant to address these issues.
While many different designs and design types have been proposed and are used in clinical practice, there is no consensus on what design or design type is the most beneficial. However, it is hypothesized, that replicating the situation that is present in healthy (asymptomatic) subjects as closely as possible, is optimal. Since the motions of the cervical spine are coupled (coupling of rotation and translation as well as multiple rotations) the optimal design of the articulating surfaces is not obvious. Therefore, this master’s thesis project aims at designing the implants articulating surfaces using parametric design optimization in LS-OPT based on finite element simulations. - Engineering and Technology
- Master Thesis
| Do you want to combine statistics, machine learning (ML), and artificial intelligence (AI) algorithms with important medical applications? Are you motivated to work with interesting real-world data and excited to implement and apply machine learning algorithms to produce personalized decision support tools? - Biology, Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Medical and Health Sciences
- Lab Practice, Master Thesis, Semester Project
| Ginkgo Introduction
Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms.
Team Introduction
The Encapsulation & Screening Foundry collaborates with other Ginkgo teams to deliver biological solutions to our partners active in industrial biotech, life sciences, agriculture, and pharma. We contribute to the success of these programs with our proprietary screening platform that enables the analysis of millions of cells and microbes to isolate candidates with specific properties. The Foundry is located at the Tech Park in Basel, Switzerland.
- Bacteriology, Enzymes, Fermentation, Biotechnology and Industrial Microbiology, Gene Expression, Genetic Engineering and Enzyme Technology, Genetic Technologies: Transformation, Site-directed Mutagenesis, etc., Medical Biotechnology, Microbial Ecology, Microbial Genetics, Molecular Evolution, Mycology
- Collaboration, Internship, Lab Practice
| Beschreibung und ökonomische Interpretation der Marktordnung eines Schweizer Agrarmarktes - Agricultural, Veterinary and Environmental Sciences
- Bachelor Thesis
| If you wear glasses, you know exactly how cumber-some it can be when your glasses fog up.
In our startup Solabs Nanotechnology, we investigate a lot of fundamental and applied phenomena to inhibit fogging. In this specific project, we employ a trans-parent, nanoscopically thin coating to prevent or re-move fog efficiently solely based on sunlight. Our coating specifically absorbs near-infrared radiation, which is not visible to the human’s eye, while it retains transparency in the visible spectrum. The absorbed energy heats up the surface and prevents fog for-mation. A global patent application for our technology is pending.
- Environmental Engineering, Materials Engineering, Mechanical and Industrial Engineering, Optical Physics
- ETH Zurich (ETHZ), Master Thesis
| This thesis focuses on fully automating the evaluation of Raman spectra in a self-driven thermodynamics lab to accelerate the development of sustainable chemical processes or novel heat pump concepts. By integrating Machine Learning (ML) with advanced spectral evaluation algorithms, the aim is to achieve complete lab autonomy. The methodology combines data-driven and physically-based approaches, including synthetic spectrum generation for ML training. - Biomedical Engineering, Chemical Engineering, Mechanical and Industrial Engineering, Physical Chemistry, Physics
- Master Thesis
| You will work on a system to analyze the dental drill that is in use. Shape, size and wear level of the dental drill have to be recognized. - Engineering and Technology
- Master Thesis
| Buildings are a major contributor to global energy consumption. Better building automation can help reduce the energy consumption and thus the operating cost of a building. This, however, comes at the cost of installing additional sensors and actuators. The goal of this project is to find the optimal trade-off between the two with the exciting real-world example of Empa's famous Nest building. - Control Engineering, Electrical Engineering
- Applications (IfA), Energy (IfA), Master Thesis
| The aim of this project is to develop a camera-based solution for motion correction of cerebrovascular 4D flow MRI, including hardware development and (deep learning-based) data analysis. - Biomedical Engineering, Computer Vision
- Bachelor Thesis, Master Thesis
| The project aims to explore the bio-fabrication of mycelium-based composites and knitted textiles for architecture and construction. Specifically the textile is used as a growing substrate for mycelium material, offering a sustainable and biodegradable building material and structural system that is strong in both tension and compression. - Biomaterials, Composite Materials, Fermentation, Biotechnology and Industrial Microbiology
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Other specific labels, Semester Project
| Machine learning for smart insect rearing for urban food waste management- Internship at the Singapore-ETH Centre - ***Please note that the internship takes place in Singapore*** - Animal Production, Artificial Intelligence and Signal and Image Processing, Biological Mathematics, Chemical Engineering
- Internship
| Biological patterns and biocommunication in insect rearing for urban food waste management-Internship at the Singapore ETH Centre - Animal Production, Biochemistry and Cell Biology, Chemical Engineering, Ecology and Evolution, Environmental Sciences
- Internship
| In this project we will design a robust MPC controller for flexibility in supply chains. The objective is to guarantee better response to abrupt changes in demand. Specifically we will design a MPC controller that optimally tunes the flexibility, namely the capability of a firm to substitute and reroute products along existing pathways. By enhancing flexibility the system can effectively mitigate the impact of disruptions. - Electrical and Electronic Engineering, Information Storage, Retrieval and Management, Information Systems Management, Mathematical Sciences, Mechanical and Industrial Engineering, Systems Theory and Control
- Master Thesis
| The thesis project deals with the powder flow optimization and fine control for AMLZ High-Speed Laser Cladding machine. - Engineering and Technology
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis
| Everyone sits. We spend more time seated than sleeping or walking, and today's human behavior shows this trend is growing. Moovtech technology aims to help recover from sedentary back pain as well as strengthen core and spinal muscles to prevent future health issues. The Moovlab technology (Moovtech) and the revolutionary PVOT dynamic motion chair show high potential for improving people's lives and health, as well as potentially stimulating brain activity and work productivity. Additionally, sitting on a PVOT chair during work hours (home office or corporate setting) has the potential to prevent chronic pains in the long term. The motion initiated by Moovtech simulates pelvic movement when walking. The aim of this internship is to equip this innovative office chair with sensor technology to analyze the sitting behavior and usage of this novel chair. This work will serve as the foundation for planning a larger study and understanding the expected data outcomes. - Engineering and Technology, Medical and Health Sciences
- Internship
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