Explore current openings and semester project topics. If you are interested, apply using the link below.
Propose a system where the prosthetic battery can be easily removed and charged safely and efficiently using a dedicated charging solution.
Apply nowEnhance safety and reliability by implementing a software-controlled battery disconnect system.
Apply nowCreate a physical model of a below-elbow residual limb based on a provided 3D scan.
Apply nowDevelop a complete control module for each finger of a hand prosthesis, including motors, gearboxes, sensors, and an electronic control board. Each module would include three motors with its dedicated control system and be directly connected to a finger mechanism. We are looking for 2 students, one for the mechanical part and one for the electronic part.
Apply nowIn this role, you will design an advanced signal processing and machine learning pipeline to spatially align EMG signals and resolve crosstalk across different electrode placements. By leveraging blind source separation techniques to extract muscle synergies, your algorithm will ensure consistent, highly accurate movement decoding between different user recording sessions. The ideal candidate is highly autonomous and possesses a strong background in signal processing, machine learning, and basic EMG analysis.
Apply nowIn this role, you will lead a comparative study to optimize a high-density (HD-EMG) bracelet, identifying the sweet spot between sensor miniaturization and signal integrity. You will experimentally validate electrode morphologies, spacing, and topologies—such as comparing active versus passive technologies—to minimize crosstalk and maximize decoding precision. This position is ideal for a student with a strong background in bio-instrumentation and prototyping who is ready to bridge the gap between electronic design and mechanical constraints.
Apply nowElevate the user experience of our bionic prosthesis by transitioning from rigid, bulky sensors to a high-density, flexible electrode array. In this role, you will design and manufacture a flexible wearable bracelet that conforms to the unique anatomy of a patient’s limb, ensuring consistent skin contact and mechanical stability during movement. Your work will involve researching conductive textiles or elastomers, optimizing breathability for all-day comfort, and solving the complex engineering challenge of interfacing stretchable tracks with rigid electronics. This project is a perfect fit for a student with expertise in CAD (Fusion360), microfabrication, and PCB design who wants to push the boundaries of bio-integrated hardware.
Apply nowAddress the "dynamic limb" challenge by engineering a compliant suspension system for our bionic arm's EMG sensors. In this role, you will design an adaptive interface—using springs, flexures, or specialized foams—to maintain constant electrode-to-skin contact as muscles expand and contract. Your goal is to eliminate signal dropouts and user discomfort by decoupling the rigid prosthetic socket from the moving limb. This position is perfect for a student skilled in Fusion360 and prototyping who enjoys solving the complex mechanical-to-electronic boundary problems inherent in wearable medical devices.
Apply nowBridge the gap between robotic prosthetics and human sensation by designing cutting-edge haptic feedback protocols for patients with sensory loss. In this role, you will develop experiments to characterize how different stimulation modalities—such as vibration, pressure, and temperature—affect a user’s sense of "embodiment" and control. You will be responsible for the full pipeline: from selecting sensors (FSRs) and actuators to writing embedded code and conducting real-world data collection sessions with patients. This position is ideal for a student with a background in embedded systems and control theory who is passionate about the human-centered side of biomedical engineering.
Apply nowThis project aims to assess the feasibility of detecting specific motor commands using Logitech’s EEG earphones. We already have an experiment designed in-house which captures neural signals associated with motor imagery and execution, moving from simple "movement vs. no-movement" classification, followed by more fine-grained movement decoding. An extension can be directional or trajectory decoding (e.g. relative to the initial position, in which direction is the hand or arm moving). In practice, this could be used for medical applications, such as the control of an arm prosthesis, or for novel, digital commands within the Logitech ecosystem. The project will be accomplished using a Logitech EEG-headphones prototype for data collection and processing. Applicant must be familiar working with embedded devices and programming in C/C++.
Apply now