ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC)| Acronym | RESC | | Homepage | https://resc.ethz.ch/ | | Country | Switzerland | | ZIP, City | | | Address | | | Phone | | | Type | Academy | | Parent organization | ETH Zurich | | Current organization | ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC) | | Child organizations | | | Members | |
Open OpportunitiesProject Objective:
This project aims to develop a new method to integrate depth perception into robots.
Specifically we are tackling the task of navigation and locomotion for our legged robot ANYmal.
Instead of training RL policies from scratch, we would like to understand the potential performance impacts by using self-supervised training, e.g. using DINO, for monocular depth images. The training may consist of leveraging existing datasets and focuses on learning a useful representation that includes not only geometric hints but potentially also semantic information from depth analog to the recent advantages achieved using RGB images.
- Computer Hardware, Computer Perception, Memory and Attention, Computer Software, Computer Vision, Electrical and Electronic Engineering
- Master Thesis, Semester Project
| 12-lead electrocardiograms (ECGs) are still solely documented on paper in many hospitals, especially in the Global South. These physical paper records provide a multitude of conditions recorded in many different countries. Our lab has access to a dataset with more than 8000 patient’s ECG photos / scans of 12-lead signals printed onto physical paper sheets. The dataset comprises 12-lead ECG image records from more than 35 hospital sites across Europe. The primary objective of this project is to develop an automated digitization pipeline from raw image scan in .png format towards 12 vectorized ECG time series in WFDB format. - Computer Vision, Engineering and Technology, Medical and Health Sciences
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| Foundation models are a breakthrough in the field of artificial intelligence. These models are characterized by massive size, reaching billions (even trillions) of parameters, and by the ability to be adapted to a wide variety of tasks without needing to be trained from scratch. The development of these models marks a pivotal shift in AI research and application, pushing the boundaries of what machines can understand and do. However, due to the huge size of foundation model, they are very demanding in terms of computation, memory footprint and bandwidth. For this reason, foundation models face significant computational challenges. These models are typically trained on massive clusters equipped with thousands of advanced GPUs. Moreover, they require cloud services for inference as well. - Artificial Intelligence and Signal and Image Processing
- ETH Zurich (ETHZ), Master Thesis
| We are working toward robots that transform their shape adapt to new tasks and environments.
This project will entail developing control policies in simulation and deploying them on hardware, with the goal of controlling a quadruped that can change the shape of its legs to accomplish new and useful tasks (see attached image a). - Intelligent Robotics, Robotics and Mechatronics, Simulation and Modelling
- Master Thesis, Semester Project
| Non-invasive, focal drug delivery in a controlled, reliable manner can lead to breakthroughs in the treatment of brain disorders. We recently developed a unique technology based on focused ultrasounds that allows for the efficient delivery of small molecules to specific brain targets. Yet, ensuring safe and effective transmission of ultrasound energy is challenging in the presence of highly-aberrating media like the skull. This project will involve the development of closed-loop algorithms and hardware for the adaptive, real-time control of ultrasound intensities during therapy. This will ensure maximally-effective drug delivery while minimizing potential harm to the target tissue. - Engineering and Technology, Medical and Health Sciences
- Master Thesis, Semester Project
| Wavemap is a multi-resolution volumetric mapping framework. By integrating its 3D maps with RL pipelines, we want to enable robots to navigate in complex environments. Future semantic support will enable advanced applications like urban navigation and safe traversal of hazardous terrains. - Intelligent Robotics
- Master Thesis
| The Laboratory of Orthopedic Technology has recently developed a novel joint implant and is undergoing optimization of the manufacturing process. We are looking for a master's student who is passionate about medical devices and mechanical design to join us for a semester project.
Objectives:
• Design different molds for material casting using SolidWorks or Fusion 360.
• Optimize implant design using matlab or Python.
• Mechanical testing of the implant including fatigue test.
Your Profile:
• Strong knowledge in mechanical design and drawing skills.
• Hands-on and detail-oriented.
• Experience with SolidWorks or Fusion 360, as well as Python or Matlab. - Biomechanical Engineering
- ETH Zurich (ETHZ), Semester Project
| This project explores how gamification elements in smartphone applications can keep patients engaged during unsupervised at-home physical therapy. Integrated with the upper-limb rehabilitation robotic device ReHandyBot, the RehabCoach app currently tracks basic metrics like time spent with the device and exercise levels. However, to improve adherence and motivation, this project aims to redesign the feedback system, incorporating features such as badges and personalized progress visualizations. By enhancing these features, the goal is to support patients in staying engaged and committed to their therapy regimens, ultimately improving long-term outcomes. - Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The Laboratory of Orthopedic Technology at ETH Zurich is currently optimizing the manufacturing process for a novel joint implant. We are looking for a master's student who is passionate about medical devices and polymer science to join our team for a semester project or master's thesis.
Project Focus: The selected candidate will work on optimizing the performance of a hydrogel material that is a key component of the cartilage replacement implant. The project will involve:
• Investigating polymer synthesis and formulation techniques to enhance hydrogel performance.
• Developing testing protocols to evaluate the hydrogel’s effectiveness in mimicking natural cartilage behavior.
- Organic Chemical Synthesis
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| Develop and test a micro-Multiphysics Agent-Based (micro-MPA) model to simulate cellular interactions and mechanical stimuli during bone regeneration and adaptation.
- Engineering and Technology
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
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