Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- Nature Careers
- Technical University of Munich
- Leibniz
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- DAAD
- Heidelberg University
- WIAS Berlin
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- University of Tübingen
- Universität Düsseldorf
- 2 more »
- « less
-
Field
-
topics in semiconductor technology and power electronics. The mission of the »Modeling and Artificial Intelligence« department is to optimize processes, components and systems, including their reliability
-
decisions and functional consequences in neurodevelopmental disorders and brain cancer. Your Role: Develop and optimize human organoid and assembloid models for studying neurodevelopmental disorders and brain
-
spend either 6 or 3 months in Bochum. During this period, CAIS finances their leave from work through compensation or grants. Individual offices and meeting rooms with modern facilities provide optimal
-
Implementation, further development and adaptation of AI models and research prototypes for the annotation and scoring of text data, in particular for the optimization of AI-supported teaching and learning in
-
, materials optimization, and microwave control are highly preferred qualifications Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be able
-
on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
-
should enable the corresponding production processes and environments to be automatically initialized, processing areas to be generated and the optimal processing tools and their alignment to be assigned
-
energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
-
the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
-
(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based