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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
of Copenhagen and Dr Lennard Krause at MAX IV in Lund. Your supervisors provide complementary expertise in mathematics, modern crystallography and machine learning, with opportunities to interact with OlexSys
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of compact robot models. The challenge is building capable robot intelligence with limited real robot data and compute. Interaction data is costly and slow to collect, while deployment requires real-time
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prediction to systems that reason, plan, interact and act in the physical world. This PhD addresses efficient long-horizon task execution in Physical AI—complex tasks needing sequences of decisions, subgoals
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