Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- Leibniz
- Constructor University Bremen gGmbH
- Deutsches Elektronen-Synchrotron DESY •
- GFZ Helmholtz-Zentrum für Geoforschung
- Heidelberg University
- Helmholtz Zentrum Hereon
- Helmholtz-Zentrum Hereon
- Leibniz-Institute for Food Systems Biology at the Technical University of Munich
- Max Planck Institute for Molecular Genetics •
- Nature Careers
- Saarland University •
- TU Dortmund
- University of Potsdam •
- University of Siegen
- cellumation GmbH
- 7 more »
- « less
-
Field
-
-related traits, and heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a
-
and individually, for example through training opportunities and the structured JuDocS program for doctoral candidates: https://www.fz-juelich.de/en/judocs In addition to exciting tasks and a
-
edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
-
, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
-
rerum naturalium, abbreviated to Dr rer nat) or the academic title PhD. The Department of Mathematics and Computer Science confers the academic degree of Dr rer nat. Alternatively, women can be awarded
-
processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
-
two companies. The project has partners from eight different EU countries. All 15 PhD projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications
-
or functional properties. Collaborating closely with experimental partners to integrate decision-making algorithms into real scientific workflows. Publishing results in high-impact machine learning and
-
yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
-
algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in