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The Laboratory for Translational Engineering led by Prof. Giovanni Traverso at the Broad Institute of MIT and Harvard, and Brigham and Women's Hospital, Harvard Medical School currently has several openings students interested in interdisciplinary research in translational engineering. We are pushing the frontier of medical technologies by bridging the gap between engineering and clinical medicine. - Engineering and Technology
- Internship, Master Thesis, Semester Project
| Neuromorphic computing calls for innovative memory elements that mimic brain-like efficiency. Ferroelectric capacitors (FeCAPs) based on hafnium zirconium oxide (HZO) have emerged as promising candidates due to their nonvolatile polarization states, high endurance, and low-power switching. However, to harness HZO FeCAPs in neuromorphic circuits, a robust device-to-circuit modeling framework is needed. This project addresses the gap by bridging detailed device physics and circuit-level simulation for HZO-based FeCAPs.
We propose to develop a comprehensive modeling flow that spans from TCAD device simulation to circuit integration. First, a physics-based TCAD model of the HZO FeCAP will be built and calibrated against experimental electrical data using Python-driven optimization, ensuring the model accurately captures ferroelectric behavior. Next, the calibrated device model will be distilled into a SPICE-compatible compact model (implemented in Verilog-A) for efficient circuit simulations. This compact model will enable designers to simulate neuromorphic architectures incorporating FeCAPs and assess performance impacts. Additionally, the influence of device geometry (such as ferroelectric layer thickness and capacitor area) on FeCAP behavior will be investigated to guide design optimizations. By leveraging TCAD, Verilog-A, and SPICE simulations in a unified flow, the project will produce a validated multi-scale model. This outcome is expected to accelerate the design-technology co-optimization of ferroelectric-based neuromorphic systems, providing valuable insight into how device-level engineering affects circuit-level functionality and efficiency. - Computer Hardware, Electrical and Electronic Engineering, Interdisciplinary Engineering, Materials Engineering
- Bachelor Thesis, Collaboration, ETH Zurich (ETHZ), Master Thesis, Semester Project
| This project investigates the trade-offs between analog and digital implementations of spiking neurons within a state-of-the-art 7nm FinFET technology node, utilizing the open-source ASAP7 PDK. By designing and benchmarking both Leaky Integrate-and-Fire (LIF) and Izhikevich (IZ) neuron models in analog and digital domains, the study aims to evaluate their respective advantages concerning power consumption, area efficiency, and functional complexity. The outcomes will provide valuable insights for future neuromorphic circuit designs targeting low-power, real-time applications. - Computer Hardware, Electrical and Electronic Engineering, Interdisciplinary Engineering
- Bachelor Thesis, Collaboration, ETH Zurich (ETHZ), Master Thesis, Semester Project
| Basierend auf Ihren Kenntnissen aus der Vorlesung «Optimierung landwirtschaftlicher Produktionssysteme» erstellen Sie ein Optimierungsmodell in Excel oder R und beantworten damit eine von Ihnen erarbeitete Forschungsfrage. - Agricultural Economics, Environmental Sciences, Operations Research
- Bachelor Thesis
| The Center for Proton Therapy (CPT) at PSI is the world leader in the development and clinical implementation of pencil beam scanning proton therapy. We are looking for talented and motivated students with a background in physics, engineering and computer science to join our research program. - Engineering and Technology, Physics
- Bachelor Thesis, Master Thesis, Semester Project
| Biohybrid robots integrate living cells and synthetic components to achieve motion. These systems often rely on engineered skeletal muscle tissues that contract upon electrical stimulation for actuation. Neuromuscular-powered biohybrid robots take this concept further by integrating motor neurons to induce muscle contractions, mimicking natural muscle actuation. In our lab, we are developing neuromuscular actuators using advanced 3D co-culture systems and biofabrication techniques to enable functional macro-scale biohybrid robots. - Biochemistry and Cell Biology, Biomaterials, Biomechanical Engineering, Biotechnology, Materials Engineering, Mechanical Engineering
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| This master's thesis aims to develop a model-based optimal control strategy to accelerate the measurement process on a turbocharger gas-flow testbench. By modeling the temperature dynamics of the testbench and turbocharger housing, and identifying parameters from existing data, the project will enable faster transitions between operating points. The optimized control strategy will be compared to current methods, and additional focus will be placed on minimizing overall measurement time by optimizing the sequence of test points. The work supports Accelleron's efforts in efficient turbocharger characterization. - Mechanical and Industrial Engineering, Simulation and Modelling
- Master Thesis
| 3D printing has revolutionized the way objects are designed and fabricated across a wide range of industries—from aerospace and automotive to healthcare and consumer products. It enables rapid prototyping, complex geometries, customized solutions, and recently bioprinting of living tissues that are difficult or impossible to achieve with traditional manufacturing methods. Every 3D printing method has certain drawbacks, often related to resolution, material compatibility, speed, or scalability. The ongoing search for new approaches aims to overcome these challenges and expand the potential of the technology. We have developed and demonstrated a proof of concept for a novel printing approach, and are now seeking to advance it into a fully functional prototype. - Biomedical Engineering, Printing Technology
- Master Thesis, Semester Project
| This internship offers practical research experience in speech and audio-based AI at the University of Zurich’s KrauthammerLab. The focus is on building systems that can understand and generate spoken language in natural and expressive ways. - Computer-Human Interaction, Speech Recognition
- Internship
| MA project to commission and test a 10 kW converter prototype for wireless power transmission - Electrical Engineering
- Master Thesis, Semester Project
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