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engineering, computer science or electrical engineering, with good grades. Experience in scientific work, project proposal writing and team leadership are part of your repertoire. In addition, you are
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure
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available in the further tabs (e.g. “Application requirements”). Programme Description The Boehringer Ingelheim Fonds travel grants are aimed at doctoral, MD and post-doctoral students who pursue experimental
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scenarios and analyse their data to validate the coupled biogeodynamic model. to interact with members of the biogeodynamics modelling group and program area 4 at regular meetings as well as with others from
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at internal and external meetings. Successful applicants: had a completed university degree (e.g. master, diploma) in biology, neurobiology, biophysics, physics or engineering and already hold or will complete
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include the University of Oxford, Imperial College London and Ukrainian and British policymakers. What we look for PhD in a policy-related field (e.g., public policy, political economy, economics, political
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the following areas: PhD in mechanical/electrical engineering, robotics, computer science, or a comparable field, Experience in self-reliant managing of research projects (financial and administrative) and
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coordination with Prof. Dr. Harald Sack. Qualifications and Skills: A very good PhD degree in computer science or a comparable discipline. Very good software engineering skills. Excellent written and spoken
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management, (organizational) psychology, sociology, economics, business informatics, or related subjects, • with a strong passion for entrepreneurship and/or family business research, • with a solid knowledge