Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Technical University of Munich
- University of Tübingen
- Leibniz
- Fritz Haber Institute of the Max Planck Society, Berlin
- Heidelberg University
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- Forschungszentrum Jülich
- Free University of Berlin
- Helmholtz-Zentrum Berlin für Materialien und Energie
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- 1 more »
- « less
-
Field
-
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
-
Postdoctoral Researcher and Coordinator of Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” (m/f/d, E13 TV-L, 100%, 3 years) Tasks and responsibilities Research
-
through soft, disordered materials, including auto-regulated networks, composite soft solids, and exotic photonic biomaterials. The lab has two fully funded PhD and/or postdoctoral positions available
-
planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
-
skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be
-
. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
-
Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
-
or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
-
or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
-
Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics