Sort by
Refine Your Search
-
Listed
-
Employer
- ETH Zurich
- University of Basel
- Nature Careers
- ETH Zürich
- Empa
- HES-SO Genève
- CERN
- EPFL - Ecole Polytechnique Fédérale de Lausanne
- Graduate Institute of International and Development Studies, Geneva;
- 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
-
development for quantum key distribution and (2) TFLN circuit development for quantum enhanced precision measurements. This PhD project aims to further advance the nanofabrication of TFLN photonic circuits
-
-scale geospatial and Earth system datasets, within the NCCR CLIM+ program. The role bridges climate science and AI, developing novel methods for climate data analysis, downscaling, and synthesis using
-
The successful PhD candidate will contribute to the scientific development, implementation, and evaluation of a mobile app. Working within a highly multidisciplinary team of psychologists
-
. Empa is a research institution of the ETH Domain. The Laboratory of Advanced Materials Processing (LAMP) is a multidisciplinary research unit that develops innovative functional modification of materials
-
to integrate cutting-edge multi-sensor fusion and AI technologies? Join our young and dynamic team at the Chair of Space Geodesy , led by Prof. Benedikt Soja . We are at the forefront of developing innovative
-
for such purposes in a wide spectrum of industries, with significant breakthroughs in computer vision, natural language processing, and intelligent control. This PhD project aims to develop foundation models (FMs
-
, are rare. This project exploits the unique monitoring capabilities of the Bedretto Underground Laboratory to investigate these processes and to develop experimentally validated guidelines for safer shut-in
-
develops uniquely interdisciplinary design and history and theory research for landscape architecture. Through geohistorical practice, we integrate tools from natural sciences and humanities with those
-
innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. Project background We are looking for a motivated Machine Learning Scientist to join the development team
-
of statistical seismology and machine learning. This position is part of two EU-funded projects: GeoTwins , which focuses on creating digital twins for geothermal systems, and Earth-AID, which aims to develop