Sort by
Refine Your Search
-
Listed
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Leibniz
- Free University of Berlin
- Nature Careers
- Forschungszentrum Jülich
- ;
- Technische Universität München
- DAAD
- Humboldt-Stiftung Foundation
- Max Planck Institute for Brain Research, Frankfurt am Main
- Max Planck Institute for Plasma Physics (Garching), Garching
- RWTH Aachen University
- 3 more »
- « less
-
Field
-
of the novel methods created within our research group. Your primary tasks will include: - Assisting in the research taking place in our group. - Collaborating with our researchers to translate new algorithms
-
. For the development and implementation of new algorithms in the field of 3D model generation, scene design and visual effects and in the development of AR/VR applications, we are looking for committed, independently
-
you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
-
Mathematics at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo
-
) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
-
laboratories and testbeds for optical communications in Europe and maintains a complete library of optical communications digital signal processing algorithms. We are recruiting students in the field of digital
-
strategies, and cross-functional collaboration — shaping the future of quantum computing. We holistically address business-relevant challenges using innovative quantum computing algorithms and demonstrate
-
dynamics or Hamiltonian eigenstates with classical and quantum algorithms Comparison of quantum algorithms with classical baselines Analysis and documentation of results What you bring to the table Student
-
will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable