Sort by
Refine Your Search
-
Listed
-
Employer
- ETH Zurich
- University of Basel
- Nature Careers
- ETH Zürich
- Empa
- HES-SO Genève
- Academic Europe
- EPFL - Ecole Polytechnique Fédérale de Lausanne
- GRADUATE INSTITUTE
- Paul Scherrer Institut Villigen
- School of Architecture, Civil and Environmental Engineering ENAC, EPFL
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL
- University of Zurich
- University of Zurich, Institute of Education
- 4 more »
- « less
-
Field
-
PhD fellowship/scholarship at Environmental Geosciences, University of Basel, Switzerland within the PhD Program Environmental Sciences . The position is available from 1 June 2026 or later. Research
-
School of Architecture, Civil and Environmental Engineering ENAC, EPFL | Switzerland | about 1 month ago
19 Mar 2026 Job Information Organisation/Company School of Architecture, Civil and Environmental Engineering ENAC, EPFL Research Field Computer science Technology Researcher Profile Leading
-
100%, Locarno, fixed-term Recent advances in AI-based weather prediction have demonstrated remarkable skill and computational efficiency. However, most current machine-learning weather prediction
-
close collaboration with courts and partners across Switzerland. We are looking for Research Assistants (Law, Computer Science, or related fields). Job description We are looking for highly motivated
-
of material science. Examples are the use and development of muon instrumentation for the study of quantum and energy materials. The research program of this new professorship will be able to take advantage
-
and professionals across emerging areas like machine learning, cyber security, climate risk, distributed ledger technology, and quantum computing and translates that expertise into integrative research
-
16 Apr 2026 Job Information Organisation/Company GRADUATE INSTITUTE Research Field Juridical sciences Researcher Profile Leading Researcher (R4) Application Deadline 15 May 2026 - 00:00 (UTC
-
, with strong expertise in tissue remodeling and regeneration, molecular oncology, genome engineering, functional genomics, metabolomics, and computational biology, providing an ideal setting for impactful
-
interest in data-intensive systems. You bring a solid foundation in software or data engineering, typically developed through a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or
-
or mechanical engineering, or CS Solid knowledge of computer vision and ML, particularly anomaly detection methods Experience with multimodal data (e.g., image + time series, sensor fusion) is a strong ad-vantage