Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- DAAD
- Fraunhofer-Gesellschaft
- Humboldt-Stiftung Foundation
- Leibniz
- Nature Careers
- Forschungszentrum Jülich
- Helmholtz-Zentrum Geesthacht
- Hannover Medical School •
- Heidelberg University
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Meteorology •
- Max Planck Institute for Sustainable Materials •
- Technische Universität Berlin
- University of Bremen •
- University of Münster •
- University of Tübingen
- 9 more »
- « less
-
Field
-
Kolter, Tjibbe Donker and Philipp Henneke analysis of multiscale single cell ‘omics data in in experimental and human models reference genome and transcriptome assembly and annotation across species
-
) on Foundation Models and/or Deep Learning for Imaging Problems. The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing. The current focus is
-
different sources (observation, model output) You are interested in applying methods for automated detections of weather (e.g., cyclones, jets, frontal systems) which can include machine learning methods You
-
screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot
-
of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for RTL design (VHDL, Verilog) of digital blocks and
-
Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
-
of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do The complete design and implementation of analog circuits including
-
of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Design innovative memory arrays for non-volatile memories Develop
-
of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for writing Verilog/ VHDL code for AI blocks Perform
-
-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training