Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Leibniz
- Forschungszentrum Jülich
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- University of Tübingen
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- DAAD
- Friedrich Schiller University Jena
- Fritz Haber Institute of the Max Planck Society, Berlin
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- University of Duisburg-Essen
- University of Paderborn
- WIAS Berlin
- 8 more »
- « less
-
Field
-
`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
-
master's degree (or equivalent diploma) and a PhD in meteorology, oceanography, or a related natural or geoscientific discipline with significant physical and mathematical components. It is essential
-
field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
-
, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
-
available in the further tabs (e.g. “Application requirements”). Programme Description The Boehringer Ingelheim Fonds travel grants are aimed at doctoral, MD and post-doctoral students who pursue experimental
-
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
-
experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs), calculus of variations, optimal control, who is willing to engage in innovative
-
. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
-
. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
-
-quantum cryptography and coded computing (1 postdoc, 1 PhD, Antonia Wachter-Zeh, antonia.wachter-zeh@tum.de) • Theory for communication systems beyond Shannon's approach (1 postdoc, 1 PhD, Christian Deppe