Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Technical University of Munich
- Leibniz
- Nature Careers
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- University of Tübingen
- Ludwig-Maximilians-Universität München •
- University of Göttingen •
- University of Stuttgart •
- Universität Hamburg •
- Goethe University Frankfurt •
- Humboldt-Stiftung Foundation
- Karlsruhe Institute of Technology •
- University of Münster •
- Bielefeld University •
- Carl von Ossietzky University of Oldenburg •
- Deutsches Elektronen-Synchrotron DESY •
- FAU Erlangen-Nürnberg •
- Friedrich Schiller University Jena •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Extraterrestrial Physics •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institutes
- Max Planck School of Cognition •
- RPTU University of Kaiserslautern-Landau •
- Technical University of Darmstadt •
- Technische Universität Berlin
- Technische Universität Berlin •
- University of Bamberg •
- University of Bayreuth •
- University of Bremen •
- University of Education Freiburg •
- University of Kassel •
- University of Regensburg •
- 26 more »
- « less
-
Field
-
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
-
At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
-
Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
-
tasks: Computationally design and simulate neuromorphic hardware including novel materials, devices and circuits. Implement bio-inspired learning algorithms on said hardware. Collaborate with
-
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
-
backend tool such as RC compiler, Design compiler, Cadence Genus, Innovus, Encounter Prior knowledge in at least one of the following areas as an advantage: deep learning hardware development memory
-
main focus on the development of control software. ▪ You will design and implement advanced control and readout protocols and optimize experimental characterization workflow,s leveraging machine learning
-
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
-
tomography. To this end, you will utilize pattern matching to identify characteristic sample features both in X-ray tomographic images and the focussed-ion beam workstation in which the samples for electron
-
are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we