Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Forschungszentrum Jülich
- Heidelberg University
- Leibniz
- Karlsruher Institut für Technologie (KIT)
- Catholic University Eichstaett-Ingolstadt
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Max Planck Institute for Evolutionary Anthropology, Leipzig
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Solid State Research, Stuttgart
- TU Dresden
- Technische Universität Ilmenau
- University of Tübingen
- Universität Freiburg, Historisches Seminar
- 6 more »
- « less
-
Field
-
the risks and success rates of real, patient-specific aneurysms, their treatment options, and long-term prognosis. The project is complemented by contributions in machine learning, such as the rapid
-
collaborative project between the Ralser lab and the Vingron Lab. This joint endeavor aims to explore phenotype predictions based on large proteomic datasets and machine learning approaches. We are seeking a
-
. The position is part of the project “Understanding of, and Explanations with, Large Language Models”, which is funded by the Volkswagen Stiftung and associated with the Cluster of Excellence “Machine Learning
-
theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
-
your technical goals. Collaboration opportunities with the Nanoscale Science Department and the European industry leaders in electron microscopy and machine learning, as well as financial support to
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 23 days ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
-
Max Planck Institute for Solid State Research, Stuttgart | Stuttgart, Baden W rttemberg | Germany | 2 months ago
Planck Society to support your technical goals. Collaboration opportunities with the Nanoscale Science Department and the European industry leaders in electron microscopy and machine learning, as
-
is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
-
to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling
-
to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling