40 computational-physics-"https:"-"https:"-"https:"-"https:"-"Caltech" research jobs at Nature Careers in Denmark
Sort by
Refine Your Search
-
Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
-
We are seeking applicants for a 2 year-postdoctoral position to join us in the Optomechanics group at the Department of Physics and Astronomy in order to work with nanoguitar optomechanical
-
The Department of Biomedicine, Faculty of Health, Aarhus University invites applications for a postdoctoral position in Computational Spatial Proteomics and Multi-Omics Integration, starting 1
-
at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
-
DTU Tenure Track Researcher in Computational Heterogeneous Catalysis – DTU Physics A scientific staff position is open in the Catalysis Theory Center at the Department of Physics (DTU Physics) and
-
We are seeking applicants for a 2-year postdoc in Ultrafast X-ray probes of Quantum Materials to join us at the Department of Physics and Astronomy. Starting Date and Period The position is for 2
-
-year period and is funded by a Carlsberg Foundation Accomplish Grant to Prof. Nanna B. Karlsson. About the position This position is part of the research programme REGLA, investigating the physical
-
sustainable process development. Opportunities to contribute to an ambitious research program (HyperCap) advancing novel carbon capture technologies toward pilot-scale demonstration. A supportive and
-
University, Department of Biological and Chemical Engineering (AU-BCE) encompasses some 200+ employees and five educations. Position is embedded in the section for Process & Materials Engineering, where
-
, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer