Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Heidelberg University
- Karlsruher Institut für Technologie (KIT)
- Leibniz
- Max Planck Institute for Astrophysics, Garching
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Evolutionary Biology, Plön
- Nature Careers
- Technische Universität Dortmund
- UNIVERSITY OF TECHNOLOGY NUREMBERG
- 3 more »
- « less
-
Field
-
classical calibration pipelines, including camera models, calibration targets, and algorithms, followed by an overview of our in-house specialized methods. In parallel, you will work in experimental setups
-
related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
-
Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 2 months ago
description: The Scientific Computing Center is the Information Technology Center of KIT. The Research Group Exascale Algorithm Engineering of SCC works at the interface of algorithmics, parallel computing, and
-
) The Institute of Computer Engineering (ZITI) at Heidelberg University invites applications for one research assistant position with the possibility to do a PhD in parallel at the chair of computer architecture
-
Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 27 days ago
of subgrid models in simulations, in particular for feedback processes Creation of new reference cosmological simulation models of galaxy formation Quantification of modelling uncertainties in simulation
-
Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | 28 days ago
theoretical models and computer simulations. Adaptation of complex traits is assumed to occur through subtle frequency changes at many loci following a shift in the trait optimum, i.e. polygenic adaptation
-
program generation and optimization Verification, testing and security of software systems Explainability of AI and of software engineering Software for distributed, highly-parallel AI systems Intelligent
-
integrate linear and circular processes, enabling used products to be transformed into new generations. What you will do Implement GPU-accelerated Gaussian Mixture Model (GMM) learning in PyTorch Optimize
-
-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
-
high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling