Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Forschungszentrum Jülich
- Leibniz
- Nature Careers
- DAAD
- Free University of Berlin
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Biogeochemistry, Jena
- University of Tübingen
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- CISPA (at University of Stuttgart)
- Humboldt-Universität zu Berlin •
- Ludwig-Maximilians-Universität München •
- MPINB
- Max Planck Institute for Biology of Ageing, Cologne
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Human Development, Berlin
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Max Planck Institute for Neurobiology of Behavior - caesar, Bonn
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Max Planck Institute of Biochemistry, Martinsried
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- TU Bergakademie Freiberg
- WIAS Berlin
- 18 more »
- « less
-
Field
-
reporting skills (4) Experience in spatial data analysis using geographic information systems (GIS) and programming languages (R, Python) as well as experience in numerical model applications and multivariate
-
geographic information systems (GIS) and programming languages (e.g. Python, Matlab, R) as well as in advanced statistical methods for analyzing complex ecosystem and environmental datasets. Good knowledge
-
programmes Much of the programme coursework requires the use of statistical programmes. Most students will use R software, although some students will use other programmes, such as Python, Stata, or SAS
-
structure- and ligand-based drug design methods (e.g., docking, QSAR, classic molecular dynamics, etc.) Familiar with all aspects of protein-ligand interactions. Solid python programming knowledge and good
-
defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
-
to the table Student in the field of Computer Science, Electrical Engineering, Physics, Mathematics or another related degree program with a scientific or engineering focus Knowledge of Python/Jax/C++ Knowledge
-
Computational Pathology is preferred. A strong publication history, including but not limited to conferences such as MICCAI, NeurIPS, ISBI, ICCV, ICML, ECCV, or others. Proficiency in Python, TensorFlow/PyTorch
-
procedures A good understanding of mathematical concepts Basic knowledge in programming, e.g. C++, Python, MATLAB, R Creative thinking and interest for novel technologies Good communication skills and teamwork
-
: A qualifying university master’s degree in physics, engineering, meteorology, or a comparable field. Knowledge of fluid dynamics or nonlinear systems Experience in programming with Matlab or Python
-
good academic record and currently enrolled in a master’s program in natural science, computer science, engineering or a related field of study • Very good Python (or other) programming skills • Good