Sort by
Refine Your Search
-
the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The Section Fundamental
-
protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ Please
-
personal skills. Candidates ideally combine several of the following skills and qualifications: A very good M.Sc. degree (or equivalent) in biology, physics, computer science, maths or a similar field A
-
will be given the opportunity to develop a doctoral thesis with extensive support through the CBBS graduate program (https://cbbsgp.med.ovgu.de ). Your profile: MSc in Neuroscience, Biology, Biomedical
-
Service) applications support the C3S Agriculture Micro-site and Mediterranean Demonstrator with agronomic insights and data Your qualifications: PhD in crop science, computational environmental science, or
-
, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
-
. Information on the DFG Priority Program SPP 2322: https://soilsystems.net/ For cost reasons, application documents or extensive publications can only be returned if an adequately stamped envelope is attached
-
: development and coordination of the wind erosion monitoring program, the development and adaptation of measurement methods and modelling approaches both in the ZALF part of the project and between the involved
-
. The communication language of the lab is English. The group interacts tightly with the Research Group Cognitive Neurophysiology (PI M. Yoshida; in-vitro/in vivo electrophysiology & computational neurosciences) as
-
Computer Science, Data Science, Physics, Mathematics, Computational Biology, or related fields. Solid experience with Machine Learning / Deep Learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong