Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Leibniz
- Nature Careers
- Forschungszentrum Jülich
- ; Technical University of Denmark
- DAAD
- Fraunhofer-Gesellschaft
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- University of Paderborn
- University of Tübingen
- 2 more »
- « less
-
Field
-
teaching and curriculum development. Your qualifications PhD in computer science, data science, applied mathematics, physics, or a related field. Strong expertise in machine learning and deep learning
-
: applicants should hold a PhD degree in quantitative science such like bioinformatics, physics, computer science or a comparable field proved outstanding skills in computer science, physics, mathematics, or a
-
Fraunhofer IOSB. You will be part of a large, interdisciplinary team from the fields of production engineering and computer science and will explore fundamentally new approaches in seven sub-projects to make
-
`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
-
, Mathematics, Physics, or similar fields Broad interest in scientific topics Good knowledge of AI and applied Machine Learning Practical experience with High Performance Computing Systems as well as parallel
-
master's degree (or equivalent diploma) and a PhD in meteorology, oceanography, or a related natural or geoscientific discipline with significant physical and mathematical components. It is essential
-
Review, update, and consolidate methodologies, including Bayesian methodologies, in the context of material balance evaluation Your Profile: PhD in applied mathematics, computer science, physics, or in
-
within the biogeochemical ocean model ERGOM (https://ergom.net ). The candidate will utilize the Code Generation Tool (CGT, https://ergom.net/code-generation-tool.html ) and actively participate in ongoing
-
' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
-
scientifically curious researcher who is passionate about understanding the environment. Applicants must have a university degree (master/diploma) and a PhD in meteorology, oceanography or a related natural or