Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Technical University of Munich
- Forschungszentrum Jülich
- Nature Careers
- University of Tübingen
- Hannover Medical School •
- Leibniz
- Ludwig-Maximilians-Universität München •
- University of Göttingen •
- Brandenburg University of Technology Cottbus-Senftenberg •
- Giessen University
- Helmholtz-Zentrum Hereon
- Technische Universität Berlin •
- University of Münster •
- University of Regensburg
- Universität Tübingen
- Academic Europe
- Deutsches Elektronen-Synchrotron DESY
- Deutsches Elektronen-Synchrotron DESY •
- GFZ Helmholtz-Zentrum für Geoforschung
- Heidelberg University
- Helmholtz Zentrum Hereon
- Helmholtz-Zentrum Geesthacht
- Hertie School •
- Karlsruher Institut für Technologie (KIT)
- Lehrstuhl für Nachhaltige Thermoprozesstechnik und Institut für Industrieofenbau und Wärmetechnik
- Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Biological Intelligence •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Meteorology •
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute for the Study of Societies •
- RPTU University of Kaiserslautern-Landau •
- Saarland University •
- Technische Universität Dresden
- University Hospital Jena
- University Hospital of Schleswig Holstein
- University of Bamberg •
- University of Potsdam •
- Universität Hamburg •
- 31 more »
- « less
-
Field
-
knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
-
machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
-
for the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics.” **Positions Available** We invite applications for Doctoral Researchers with a strong background in machine learning and an
-
strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
-
Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
-
-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine learning frameworks to interrogate the relationship between brain development and cognitive
-
machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
-
, prototyping, programming (device communication, databases) Experience in the following areas is also a bonus: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show
-
and machine learning methods. Knowledge of constraint-based metabolic modelling will be considered a strong advantage. The ideal candidate is highly motivated, capable of working both independently and
-
seismicity in the area at unprecedented resolution. Leveraging and improving state-of-the-art machine learning techniques, template matching and other techniques, you will derive a high precision catalogue of