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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control
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algorithms model major sources of experimental error for control theory or co-design methods Previous works can be found under the bibliographies of Dr. Felix Motzoi and and Dr. Matthias Müller: https
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modern models beyond the worst case e.g. integrating machine learning into algorithm design. We are looking for candidates with a strong mathematical background, an excellent degree in mathematics
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PhD Researcher in Theoretical or Experimental Pragmatics / Cognitive Science (m/f/d, E 13 TV-L, 65%)
probabilistic models of pragmatic language use and interpretation. This work involves philosophical / linguistic analysis, experiments with human participants, and mathematical / statistical modeling
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The Chair of Transport Modelling and Simulation at TUD Dresden University of Technology is investigating models, algorithms and simulations to achieve an enhanced scientific understanding
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of the University of Bremen: Production Engineering, Business Studies / Economics, Mathematics / Computer Science, Physics / Electrical Engineering, and Law. Associated partners are the BIBA – Bremer Institut für
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development of artificial intelligence (AI) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms
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The Chair of Transport Modelling and Simulation at TUD Dresden University of Technology is investigating models, algorithms and simulations to achieve an enhanced scientific understanding
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training