Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Leibniz
- University of Tübingen
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Deutsches Elektronen-Synchrotron DESY
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- University of Greifswald
- Bonn University
- Constructor University Bremen gGmbH
- Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke
- FBN Dummerstorf
- Free University of Berlin
- GFZ Helmholtz-Zentrum für Geoforschung
- Heidelberg University
- Max Planck Institute for Chemistry, Mainz
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Extraterrestrial Physics, Garching
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Solar System Research, Göttingen
- 12 more »
- « less
-
Field
-
the analysis of complex biomedical data using state-of-the-art AI and agentic system approaches, as well as the development of novel machine learning and deep learning algorithms. Your work will range from
-
experimental data. Develop computational frameworks for integrating spatial and bulk multi-omics datasets. Create and apply statistical and machine learning models for feature extraction, data harmonisation, and
-
the backdrop of intensifying global geopolitical rivalry in technologies, access to resources, or financial infrastructures and military conflicts, peripheral areas in the Global East are once again being viewed
-
optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
-
economic modeling, with interests including improved spatial resolution and machine-learning-enabled approaches for policy analysis. Postdoctoral Position (f/m/d) – Integrated Assessment Modeling (Climate
-
. Antonio Scialdone’s group at Helmholtz Munich, a leading European hub for AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models
-
system) in computer science or another relevant discipline. A proven scientific focus on Artificial Intelligence (AI) & Machine Learning (ML). Experience with data analysis using ML or AI methods
-
-Phenomenology (hep-ph) , High Energy Physics , High Energy Theory , Machine Learning , Neutrino physics , Particle , Particle Physics , Particle Theory , QCD , Theoretical high energy physics , Theoretical High
-
to improve chimeric antigen receptor (CAR) T cell therapies by targeting genes and gene-regulatory processes to prevent CAR T cell dysfunction. Your tasks include but are not limited to: CAR T cell design and
-
Imaging, Machine Learning, or a related field • Demonstrated research experience in generative models for medical imaging (e.g., diffusion models, VAEs, GANs) • Publications in high-ranking journals and