Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Helmholtz Association of German Research Centres
- BAM Bundesanstalt für Materialforschung und -prüfung
- Forschungszentrum Jülich
- Institute of Molecular Biology gGmbH (IMB)
- Technische Universität Dresden (TU Dresden)
- <span lang="en">TUD Dresden University of Technology</span>
- Deutsches Elektronen-Synchrotron DESY
- Free University of Berlin
- Heidelberg University
- Max Planck Institute for Chemistry, Mainz
- Max Planck Institute for Physics, Garching
- TU Berlin
- Technische Universität Berlin
- Universität Stuttgart
- 4 more »
- « less
-
Field
-
TU Berlin seeks candidates for a PostDoc position in the field of stochastic analysis, in particular, stochastic PDEs, mathematics of machine learning, and stochastic dynamics. Our offer * PostDoc
-
quality, and health. We seek a PhD or Postdoc to work on either of the two topics: Autonomous reaction discovery: combining quantum chemistry, machine learning, and automation to chart oxidation pathways
-
at the intersection of statistical genetics, systems biology, and machine learning, with strong emphasis on methodological development.
Tasks of the PhD Student
- Develop -
Your Job This position sits at the interface between electron microscopy and machine learning. We are looking for a microscopist or physicist with substantial computational practice who wants to
-
Helmholtz Association of German Research Centres | Geesthacht, Schleswig-Holstein | Germany | about 2 months ago
existing methods (e.g. XGBoost, Gaussian Processes) - you will publish your work and contribute to open-source releases Your profile - PhD in Machine Learning, Computer Science, Physics, Environmental
-
integration of machine learning into quantum chemical methods and molecular simulation. A particular focus will be on the development, application, and evaluation of modern machine-learning methods
-
/or PhD in Computer Science, Bioinformatics, Computational Biology, Data Science, or a closely related field Strong experience in machine learning and/or deep learning, ideally with sequence models (e.g
-
opens the door to many new experiments. Through the ErUM-Data and LEAPS-funded proposals, we develop resource-efficient and reliable Al and machine learning methods to advance ML for photon science
-
-term research stays at CERN. About you: PhD in experimental particle physics, completed or nearing completion. Demonstrated experience with machine-learning methods in high-energy physics, ideally
-
<span lang="en">TUD Dresden University of Technology</span> | Dresden, Sachsen | Germany | 4 days ago
domains are e.g. signal-/image processing and machine learning.
Tasks:
- modeling and simulation of near-memory computing architectures for RISC-V processors using