Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ETH Zurich
- ETH Zürich
- University of Basel
- Empa
- Nature Careers
- University of Bern
- Universität Bern
- ZHAW - Zurich University of Applied Sciences
- Zürcher Hochschule für Angewandte Wissenschaft ZHAW
- Academic Europe
- Fluxim AG
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL
- University of Applied Sciences Northwestern Switzerland
- University of Zurich
- École Polytechnique Fédérale de Lausanne (EPFL)
- 5 more »
- « less
-
Field
-
authorities and administrations at a regional, cantonal, and national level, as well as for joining international networks focusing on studying novel forest realities. You hold a PhD and have an excellent
-
resistance and biofouling, leading to economic costs of billions of dollars annually and thousands of deaths. Biofilms are microbial communities encased in a polymeric matrix that provides mechanical stability
-
start-up or spin-off highly appreciated. Strong network in the start-up and investor ecosystem is advantageous. Exceptional organizational, communication, and project management skills. Proactive
-
Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
enable the long-term monitoring of the emissions from large point sources across the globe, which will be critical for tracking progress in reducing air pollution and achieving net-zero emissions under
-
analytical and problem-solving skills with high scientific curiosity. Ability to work independently and in a collaborative, interdisciplinary environment. Excellent communication skills in English (both
-
. Strong project management and communication skills, with the ability to contribute expertise in a collaborative setting. Fluency in written and spoken English. We are looking for a highly motivated
-
across scales, from the polymeric network and mesoscale structure to the macroscopic continuum, supported by consistent coarse-graining and homogenization strategies. Your responsibilities include
-
, carbon dioxide removal (CDR) is needed to balance residual emissions on the path to net zero and to manage overshoot through net-negative CO₂ removals. Since about four years, our group studies
-
, ensuring interoperability with the Swiss Personalized Health Network (SPHN). BMIP builds on ETH Zurich’s Leonhard Med secure research-IT platform and supports the use of artificial intelligence to advance
-
, and this process is tightly regulated by a network of chaperone proteins. At the heart of this network is Hsp90, a molecular chaperone essential for the folding and maturation of at least 20% of all