Sort by
Refine Your Search
-
Listed
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Nature Careers
- Leibniz
- Forschungszentrum Jülich
- DAAD
- DWI Leibniz-Institut für Interaktive Materialien e.V.
- Free University of Berlin
- German Cancer Research Center
- Heidelberg University
- Max Planck Institute for Molecular Biomedicine, Münster
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Technische Universität München
- 3 more »
- « less
-
Field
-
terrestrial system models, for example using data analysis methods, such as data assimilation, physical- or process-based machine learning, or deep learning algorithms Analysis of the effects of human
-
on three areas: strategy&technology (in particular deep tech such as AI, robotics, biotech), strategy&global contexts, and the theory of the firm (see www.msl.mgt.tum.de/simanagement ) We do not only
-
Computer Science, Artificial Intelligence, Materials Science, or a related field Strong programming skills in Python, ideally with experience in image processing and deep learning using PyTorch or similar frameworks
-
to research facilities in Germany and abroad Scientific writing skills evidenced in publications (for Postdocs) A deep sense of scientific curiosity and the aspiration for achieving knowledge in solid state
-
multi-omics data integration and the project will provide opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD
-
Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
-
, Genome editing tools, Regulatory mechanisms, Synthetic genomics, Genotype-to-phenotype & genomic-environment interactions, Metabolism, Single cell and spatial omics development Deep learning-enabled
-
to molecular mechanism. New experimental and computational methods, including data and deep-learning driven approaches to study complex biological processes in the context of cells, organisms, communities and
-
and development to improve clinical processes for the benefit of our clinical partners and, in the end, patients. What you will do It has been observed that deep learning models are able to identify
-
Knowledge in deep learning Experience with object detection algorithms, e.g. Yolo or Faster R-CNN Plus: first experience with 3D object detection. What you can expect Very nice supervisors, a good atmosphere