Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- DAAD
- Technical University of Munich
- Leibniz
- University of Bremen
- European Magnetism Association EMA
- Fraunhofer-Gesellschaft
- Hannover Medical School •
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Geesthacht
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Evolutionary Biology, Plön
- Max Planck Institute for Molecular Genetics •
- Technische Universität München
- 5 more »
- « less
-
Field
-
learning for dementia prediction. see here: https://ai-med.de/wp-content/uploads/2025/04/PhD_Position.pdf PhD Position: Interpretable Models for Dementia Prediction Lab for Artificial Intelligence in Medical
-
to the quantum level. In the focus are advanced techniques for the preparation of controlled atomic, molecular and cluster ensembles, combined with modern ultra-short laser techniques, as well as a variety of
-
of the characterisation techniques used in the field obtain average properties of what in reality is an ensemble of molecules. The aim of this project is to study the influence of molecular disorder on the light emission
-
understanding of the key factors that affect their performance is limited by the fact that most of the characterisation techniques used in the field obtain average properties of what in reality is an ensemble
-
. D. positions funded by the ERC (European Research Council) to work on the 'EFT-XYZ' (Effective Field Theories to understand and predict the Nature of the XYZ Exotic Hadrons) project-advanced-ERC-2023
-
) Leipzig and Leipzig University Hospital. One of the aims of PollenNet is to predict pollen levels in the air, using observations of flowering plants collected via the Flora Incognita app. Your tasks First
-
PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
important part of our personnel policy. Your tasks #analysis and bias adjustment of an existing large ensemble of regional climate model simulations for Hamburg and Heide #development of impactful heatwave
-
interfaces hosting two-dimensional electron and hole gases. Closely collaborating with experimentalists, we will develop effective models to predict the spin/orbital textures, topological textures, and
-
highly motivated candidate to develop models integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing
-
the ability to learn from experimental data and make meaningful predictions, taking AlphaFold and its highly accurate protein structure prediction as an example. However, the training of powerful AI tools