Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Leibniz
- Technical University of Munich
- Nature Careers
- Forschungszentrum Jülich
- WIAS Berlin
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Free University of Berlin
- Friedrich Schiller University Jena
- Fritz Haber Institute of the Max Planck Society, Berlin
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- University of Tübingen
- 3 more »
- « less
-
Field
-
2 Sep 2025 Job Information Organisation/Company Friedrich Schiller University Jena Department Psychiatry and Psychotherapy Research Field Neurosciences Computer science Mathematics Engineering
-
theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or
-
), the successful candidate will investigate how a high-fat diet (HFD) affects various organ systems - in particular the liver and heart, but potentially also skeletal muscle and adipose tissue - in a mouse model. In
-
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 7 hours ago
of Oldenburg Your Profile PhD in marine ecology, finalized by the start of the project Advanced statistical modeling skills including analysis of biodiversity time series and functional traits, evidenced by
-
simulation, with strong skills in mathematics Highly proficient in Matlab/Simulink for system modelling Experience with (stationary) battery storage systems is required Prior exposure to HIL systems is a
-
for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The purpose of this position is to conduct research in the field of model
-
soon as possible. The position is within the Math+ project "Anisotropic microfluids -- fluctuations, control, effective models and their numerics “. Here, we study anisotropic microfluids and the effect
-
assigned to the research project "Randomization of Surrogates for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The
-
and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
-
Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological