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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very
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between quantum computers (via Qiskit) and classical HPC resources Validate the QCS-MiMiC implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM / MM
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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for an initial period of 3 years. An extension for up to another 2 years is possible under the above-mentioned condition. The Research Group Our research activities primarily focus on developmental, cellular, and
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conditions and under the impact of the food supply chain, including food processing. In this context, the aim of the PhD project is to investigate the influence of drought stress on sulphur-containing plant
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oxide (N₂O) emissions by extensive site monitoring testing conservation practices like variable-rate fertilization, and engaging land managers through farm-based tools and a revised European nitrogen
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, their achievements and productivity to the success of the whole institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Robotics offers a full-time
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and
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conditions that enable planners to make informed and responsible trade-offs among conventions and population groups. Tasks: Independent and cooperative qualification through scientific research within