Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- DAAD
- Leibniz
- Nature Careers
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Extraterrestrial Physics, Garching
- RWTH Aachen University
- University of Tübingen
- GFZ Helmholtz Centre for Geosciences
- Humboldt-Universität zu Berlin •
- Leibniz-Institute for Plant Genetics and Crop Plant Research
- Ludwig-Maximilians-Universität München •
- MPINB
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
- Max Planck Institute for Meteorology •
- Max Planck Institute for Neurobiology of Behavior - caesar, Bonn
- TU Bergakademie Freiberg
- 10 more »
- « less
-
Field
-
and statistical data analysis Excellent written and spoken English skills Experience with TMS and proficiency in relevant software (e.g., MATLAB, R, Python, or SPSS) is an advantage Key responsibilities
-
Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with
-
simulation software, e.g., SUMO, MATSim, etc. Good command of a statistical or procedural programming language such as R, python, julia, matlab, etc. Interest in transport policy We offer We offer a full-time
-
are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C
-
publication record #excellent programming skills in Python or at least one other scientific programming language (e.g. FORTRAN, C, Matlab, R) #good knowledge of English (written and oral) #high degree
-
academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
-
occur, and how can the overloading of individual regions be counteracted? Your contribution to scientific analysis: Further develop existing energy system models in Python to accurately map and analyze
-
into account as disruptive events, and which strategies can be derived from this for a resilient system design. Your contribution to scientific analysis: Further develop existing energy system models in Python
-
language (Python/Matlab/C++ etc.) Proficiency in English, both written and spoken Ability to work independently and to work as part of a team Good reasons to join: Look forward to a unique working
-
science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough