Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Leibniz
- Technical University of Munich
- Forschungszentrum Jülich
- University of Tübingen
- Heidelberg University
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Free University of Berlin
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Molecular Biomedicine, Münster
- Ruhr University Bochum
- WIAS Berlin
- 3 more »
- « less
-
Field
-
planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
-
The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
-
Group 13 TV-H*, in the Research Group “Radicalization, Terrorism and Extremism Prevention" for the duration of three years (acc. to WissZeitVG**). Your responsibilities include: Collaborative and
-
collaboration and mutual learning access to high-performance computing a chance to contribute meaningfully to an ambitious research agenda focused on creating positive impacts for global society and future
-
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
-
, 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
-
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
-
Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
-
for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
-
to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series