Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
on leveraging modern heterogeneous computing architectures to enable large-scale, high-fidelity reacting-flow simulations. The models developed at the cell level will subsequently be coupled to module-, pack
-
30 Sep 2026 - 12:00 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related
-
and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
-
and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
-
particular strengths in nutritional and computational metabolomics, dietary biomarkers, micronutrient metal nutrition, nutritional immunology, marine food science, plant based foods, food biotechnology and
-
and neutron beamtimes; magnetometry, conductivity, EPR or solid-state NMR on air-sensitive samples. Co-authorship in studies combining experiments and theory. Qualifications PhD in Chemistry, Materials
-
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a postdoc to join our team at the Division
-
collaborate with Doctoral students and postdocs working on similar topics! About us The Department of Computer Science and Engineering , a joint department of Chalmers and the University of Gothenburg, spans
-
, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD
-
an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be