Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 13 days ago
40 research groups and some 1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics headed by (Prof. Dr
-
computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
-
algebras and quantisation, and applications to Physics such as computation of scattering amplitudes. Successful applicants will be offered great research opportunities in an excellent working environment
-
talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
-
Engineering, Computer Engineering, Computer Science, or a closely related field Strong background in robotics fundamentals: kinematics, dynamics, control, planning Proficiency in programming (C++, Python), and
-
The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
-
technologies to fundamental physics questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG
-
or Postdoc Position in Numerical Mathematics m/f/d, 100%, 2 years+ As part of the second phase of the DFG funded Priority Programme SPP2311, the Chair for Numerical Mathematics under the leadership
-
physical sciences, engineering, advanced microscopy techniques, and DNA nanotechnology. Biochemists, synthetic biologists, bioengineers, chemical biologists, chemists, or candidates with a computational
-
that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but