233 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" uni jobs in Belgium
Sort by
Refine Your Search
-
Listed
-
Employer
- Ghent University
- KU LEUVEN
- VIB
- University of Liège (ULiège)
- University of Antwerp
- Nature Careers
- Vrije Universiteit Brussel
- Vrije Universiteit Brussel (VUB)
- IMEC
- Université Libre de Bruxelles
- Université de Namur
- European Commission
- European Research Council (ERC)
- Flanders Institute for Biotechnology
- Giga Institute - University of Liege
- Hasselt University
- Louvain Drug Research Institute - Université catholique de Louvain
- Royal Observatory of Belgium - Dpt Reference Systems
- Université libre de Bruxelles (ULB)
- VITO
- 10 more »
- « less
-
Field
-
check the frequently asked questions or send an email to jobs@uantwerpen.be . If you have any questions about the job itself, please contact dr. Johan Meeusen, Tel. +32 3 265 58 36 – johan.meeusen
-
questions about the online application form, please check the frequently asked questions or send an email to jobs@uantwerpen.be . If you have any questions about the job itself, please contact prof. dr
-
the frequently asked questions or send an email to jobs@uantwerpen.be . If you have any questions about the job itself, please contact prof. dr. Mario Rinke via mario.rinke@uantwerpen.be
-
. For more information about this vacancy, please contact Prof. dr. Sophie Maussen (Sophie.Maussen@ugent.be )
-
of 12.000 euro. The bench fee remains available to the research network for the duration of the collaboration and the two subsequent years. More information Contact Team Flemish, Federal & BOF Projects
-
research into the contribution of peak concentrations to total particulate matter exposure in residential settings. You will set up measurement campaigns and process existing measurement data in
-
of the UNPACK team, you will be intensively working together in a team of 8 researchers and 4 professors. You will share your data and analyses with your co-researchers and supervisors, and engage in
-
. The research aims to translate geometric design information into quantitative estimates of manufacturing effort and cost. Methods include Graph Neural Networks, geometric deep learning, and multi-view learning
-
intensively working together in a team of 8 researchers and 4 professors. You will share your data and analyses with your co-researchers and supervisors, and engage in extensive collaborative (interdisciplinary
-
. The faculties have each developed a faculty regulation in which the financing possibilities of the Faculty Mobility and Sabbatical Fund are defined in detail. For more information, please visit your faculty's