Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Technical University of Munich
- Leibniz
- Heidelberg University
- Forschungszentrum Jülich
- University of Tübingen
- DAAD
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- ; Technical University of Denmark
- Free University of Berlin
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Molecular Biomedicine, Münster
- WIAS Berlin
- 6 more »
- « less
-
Field
-
committees is English; Very good spoken and written command of English, willingness to learn German during the duration of the employment. You can expect: A motivated, multi-cultural team of international
-
of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
-
external forcings on climate analysis of climate model output by means of classical statistical and machine-learning methods coordination of scientific workflows among project partners Your profile Master's
-
learning paradigms as well as interactive data- and model exploration with domain knowledge towards optimal performance in real-world generalization scenarios. AqQua is a large-scale collaborative research
-
learning, such as the rapid generation of realistic implant geometries or the learning of biomedical parameters from experimental or clinical datasets. Specific tasks within the project include
-
, including next generation sequencing data processing is an added advantage excellent command of written and spoken English pro-active learning and desire for career development excellent communication and
-
equal opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim to ensure
-
or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
-
, or similar disciplines Graduate students expecting to receive their PhD within six months can also apply Experience in the advanced analysis of genetic or proteomic data Interest in learning methods
-
Postdoctoral Researcher as a Junior Research Group Leader (m/f/d) - Research on and Implementation o
). The Empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation