Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
project related reports Finalize the PhD thesis at ETH Where to apply Website https://apply.refline.ch/673278/3861/ERZok1sHWtDWwnEVT-NsRT6cc6oIyFNXCgTsOHYlKz… Requirements Research FieldPhysicsEducation
-
. The deadline for applications for this Fall Call is April 20, 2026. Please submit your application to our PhD program or our MD-PhD program online. Where to apply Website https://www.fmi.ch/education-careers
-
environment. n line with our and Uni Basel values (https://www.unibas.ch/en/Research/Values-Ethics/Diversity.html ), we are committed to sustain and promote an inclusive culture, ensure equal opportunities and
-
, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net Land Take. The consortium comprises four
-
please do not hesitate to contact Stefanie Bailer (stefanie.bailer@unibas.ch ). The application deadline is January 23, 2026. The job talks and interviews are scheduled for February 2026. Where to apply
-
conditions please do not hesitate to contact Denise Traber (denise.traber@unibas.ch ). The application deadline is January 23, 2026. The job talks and interviews are scheduled for February 2026. Where to apply
-
LMU at PSI Villigen we are looking for a PhD Student in Experimental Physics Your tasks The position is available in the framework of the French-Swiss ANR-SNF Grant on the use of high-pressure and
-
embedded in Work Package 2of the ENDOTRAIN network that will explore the use of nanotechnology-enhanced electrochemical sensors for highly sensitive, selective and reversible biomarker sensing. Specifically
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description About SLICE Space utilisation plays a crucial role in understanding climate
-
more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By