Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
aspects of nuclear safely. The focus of the project is to gather essential data on the liquid source term, improve our understanding of the associated phenomena and develop tools to simulate the relevant
-
considered. Further information about the professorship can be found on our website . Questions regarding the position should be directed to Prof. David Kammer by email dkammer@ethz.ch (no applications). We
-
. Within the ITS section Scientific IT Services the group Computational & Data Science Support (CDSS) aims at bridging the gap between computational research and IT services and infrastructure provisioning
-
systems. The wide range of experiments conducted in the BedrettoLab relies on numerous sensors and data acquisition systems that monitor processes both in the tunnel and within the surrounding rock mass
-
. Further information can be obtained from the Dean of the Faculty, Pr Du Pasquier or the Head of the Department of psychiatry, Pr von Plessen. They should be submitted online by February 19th 2026 23:59
-
the legal and regulatory requirements of the position. Further information can be obtained from the Dean of the Faculty, Pr Du Pasquier or the Head of the Department of Psychiatry, Pr von Plessen
-
Topic A: Automation and Monitoring for an Internal Development Platform Abstract The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research
-
Applicants should have a strong interest in doing basic research in areas such as: Bio-inspired /Bio-hybrid Robotics, Biomechanics, Causal Inference, Computational Biology, Computer Graphics
-
to magnitude -5 at meter-scale distances. All data is acquired and processed through SeisComP. The BedrettoLab team comprises about 30 scientists from diverse disciplines and collaborates with research
-
, data-driven frameworks that enable robust monitoring and condition assessment of infrastructure fleets. By combining smart sensing with distributed intelligence and advanced stochastic modelling