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experimentation (IMD-3: Institute of Energy Materials and Devices – Photovoltaics) and high-performance computation (IET-3: Institute of Energy Technologies – Theory and Computation) towards the overarching aim
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
-like AI models which can predict DNA structures Performing experiments for validation Participation in conferences in Germany and abroad (incl. presenting your research results) Preparing scientific
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design are often too slow, costly, and inefficient to cope with the increasing complexity of performance and resource-efficiency requirements. This collaborative doctoral project brings together
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degree in physics, (physical) chemistry, or material science. Knowledge in the operation of ultrahigh vacuum equipment and using X-ray spectroscopies is mandatory. Background in photovoltaic materials
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. Transition metal-based complexes, in particular, offer rich spin properties that can be tailored through ligand design. This project aims to explore and optimize such molecules to enhance their performance as
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collaboration Initiative Structured and goal-oriented approach to work Open-minded personality, teamwork and communication skills Above-average academic performance Experience with cell and molecular biology
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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training data Building transformer-like AI models which can predict DNA structures Performing experiments for validation Participation in conferences in Germany and abroad (including presenting your research
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degree in the above mentioned or related fields. What we offer State of the art on-site high performance/GPU compute facilities A team of 30+ expert colleagues A family friendly, green campus with on-site