Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Technical University of Munich
- Leibniz
- University of Tübingen
- Forschungszentrum Jülich
- Heidelberg University
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- ; Technical University of Denmark
- DAAD
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Molecular Biomedicine, Münster
- 4 more »
- « less
-
Field
-
). The empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
-
medical professionals to translate research into real-world applications. Mentor graduate students, teach related courses, and contribute to grant writing. Requirements A PhD or equivalent in a technical
-
to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
-
tools Supervising and guiding Master and PhD students Active participation in project meetings and events Presenting and publishing the research on an international stage Your Profile: As part of our
-
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
-
-reviewed journals. The postdoctoral fellow will have the opportunity to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity
-
to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
-
projects in basic biomedical research and who wish to learn methods relevant to their current research. To this end, the grant finances the participation in practical training courses or short-term research
-
(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
-
19.07.2022, Wissenschaftliches Personal The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current