Sort by
Refine Your Search
-
Listed
-
Employer
- ETH Zürich
- University of Basel
- Empa
- Universität Bern
- ZHAW - Zurich University of Applied Sciences
- ETH Zurich
- Ecole Polytechnique Federale de Lausanne - EPFL
- University of Applied Sciences Northwestern Switzerland
- University of Berne, Institute of Cell Biology
- University of Zurich
- École Polytechnique Fédérale de Lausanne (EPFL)
- 1 more »
- « less
-
Field
-
Description As part of a new EU MSCA Doctoral Network ELEVATE (101227453), we are offering a PhD Position on “Modulating bursting activity in silicon neurons to control plasticity and attention”. Location
-
across EPFL’s international research network. Profile Master’s degree in environmental engineering, microbiology, chemical engineering, or a related discipline Demonstrated research experience
-
to think critically and a strong aptitude for interpreting/analyzing complex data. We are looking for someone with excellent organizational skills, creative, highly motivated, and fluent in English with
-
to ensure project success. Additionally, Empa offers outstanding infrastructure, career support, networking opportunities, and competitive salaries. The position is available from January 2026 or after
-
on musculoskeletal biomechanics and mechanobiology across all scales. Project background This project is part of the EU-funded Print4Life , a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof
-
in epidemiology or vice versa for an epidemiologist with strong interest & experience in complex data analysis.
-
, networking opportunities, and competitive salaries. The position is available from January 2026 or after negotiation with a duration of four years. We live a culture of inclusion and respect. We welcome all
-
protein-DNA interactions) Produce stable complexes between proteins and/or DNA Determine structures of proteins/complexes Design mutants and perturbations for in vivo experiments Perform in vivo functional
-
, aligning AI systems with complex human values, and building self-improving agents capable of autonomous learning. Our work combines cutting-edge experimentation – spanning RL, meta-learning, and robust
-
combines biology, engineering, and computational science to understand how cells organize into complex tissues. Located in Basel, the Department of Biosystems Science and Engineering (D-BSSE) provides a