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, PMID30224749 and PMID32743075 . Requirements M.Sc. degree in molecular-, cell-, structural biology, computer science, digital image analysis or related fields that included minimum six months long
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degree in computational engineering, mechanical engineering, computer science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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, computer science, or a related field with an overall grade of at least “gut” (or equivalent, e.g., cum laude) Expertise in quantum mechanics, experience with HPC, programming (e.g., Python, C / C++), and/or
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects offers a perfect opportunity for you. Today’s most pressing problems can only be solved in cross-institutional
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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. The successful candidate will receive careful mentorship both from the supervisor and from other peers through a dedicated mentorship program. Technical queries should be directed to Benedikt Jahnel
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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Universität Berlin. The position is part of the research group QUALITY.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project “PhytoM” is
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and