203 computer-"https:" "https:" "https:" "https:" "CNRS" "CNRS " "Univ" positions at Technical University of Munich in Germany
Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
26.03.2026, Academic staff Doctoral Candidate f/m/d in computational proteomics/bioinformatics with a focus on plant proteomics Candidates must hold a master´s degree in Data Engineering, Data
-
15.03.2026, Academic staff The Chair of Strategic and International Management, headed by Univ.-Prof. Dr. Thomas Hutzschenreuter invites applications as Doctoral Research Associate (m/f/d) in
-
knowledge of the German language besides English. If interested, please send your full application to the email adress provided below. At the Mechanics & High Performance Computing Group, there is an open
-
07.08.2025, Academic staff The Chair of Computational Mathematics at the Technical University of Munich (TUM) invites applications for one PhD position. The Chair of Computational Mathematics
-
Informatics Initiative (MII)/FHIR standards Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation Independently develop and implement research ideas within
-
/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically
-
-reviewed publications and talks on ntl./intl. conferences • Participation in teaching and student supervision Requirements / Your Profile • Above average university degree (MSc., Dipl. (Univ.)) in biology
-
Europe • Membership in the International Graduate School of Science and Engineering (IGSSE) and participation in the course program (https://www.igsse.gs.tum.de/en/igsse/about/) • IGSSE-funded doctoral
-
using the model iLand. The work is embedded in the BETA-FOR project (https://www.uni-wuerzburg.de/for5375/) and will collaborate closely with the Forest Economics and Sustainable Land-use Planning group
-
. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing