Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
5 Sep 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Other Engineering » Industrial engineering Engineering » Systems engineering
-
cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities for practical impact by taking the outputs from the developed machine learning
-
31 Aug 2025 Job Information Organisation/Company Uppsala universitet Department Uppsala University, Department of Information Technology Research Field Computer science Technology Researcher Profile
-
) Country Sweden Application Deadline 26 Sep 2025 - 21:59 (UTC) 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 EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description of the workplace The current
-
with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
-
to didactics of computer science. Pedagogical skills The pedagogical skills for employment as associate professor should be demonstrated by documented experience of teaching with scientific foundation
-
these transcripts into protein sequence databases. Guide the development of proteogenomics through implementation of novel algorithms and computational analysis infrastructure Development of tools to support clinical
-
University, Halmstad University, and Blekinge University of Technology. ELLIIT in Lund is spanning four departments: Electrical and Information Technology, Computer Science, Automatic Control and two research
-
into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic