Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- DAAD
- Nature Careers
- Technical University of Munich
- Catholic University Eichstaett-Ingolstadt
- Center for NanoScience Munich
- EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites
- Fraunhofer-Gesellschaft
- Heidelberg University
- Leibniz
- Max Planck Institute for Biogeochemistry, Jena
- University of Hamburg
- 1 more »
- « less
-
Field
-
The Fraunhofer Institute for Algorithms and Scientific Computing SCAI in Sankt Augustin, near Bonn, has around 180 employees who research and develop innovative methods in the field of computational
-
“Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness
-
-based tiles can be arranged and actuated to form tunable metapixels, enabling dynamic control of light at the nanoscale. This project will integrate algorithmic self-assembly and nanomechanical switching
-
, hardware-adapted optimization, and error mitigation techniques, aiming to identify requirements, limitations, and pathways for improvement of both hardware and algorithms - analyze variational ansatz
-
EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | about 5 hours ago
; Lead the functional analysis, the definition, the prototyping and the scientific evaluation of algorithms used in the level-1 and level-2 processing chains for current and future EUMETSAT satellite
-
++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
-
-1,3,3,3-tetrafluoropropene (R1234ze(E)). The position combines mechanism building and validation with algorithm and database contributions to RMG, supported by electronic-structure data from literature, and
-
-funded project “Occurrence and distribution of methylphosphonate (MPn) and its contribution to oxic methane formation in the Baltic Sea” (MPn-Baltic Sea). This project aims to improve our understanding
-
, including rare and extreme events. Quantify flood risk and improve early warning predictability in out-of-distribution conditions (climate change, land cover changes), and use explainable and causal ML
-
projects and communication Your responsibilities The Head of Unit will be responsible for the distribution of the tasks in the Unit, and oversee and support their execution: Provide mandatory introductory AI