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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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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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): Automated bidding strategies for participating in multiple markets (hydrogen, electricity) over different time scales, such as short-term forward markets and spot markets (operating in real-time). This can be
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to the success of the whole institution. At the Cluster of Excellence „Physics of Life” (PoL), the Heisenberg Chair of Biological Algorithms (Prof. Dr. Benjamin Friedrich) offers a position as Research Associate
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, their achievements and productivity to the success of the whole institution. At the Cluster of Excellence „Physics of Life” (PoL), the Heisenberg Chair of Biological Algorithms (Prof. Dr. Benjamin Friedrich) offers a
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of structures, facilitating a form-finding process driven by FEM analysis. Training deep learning algorithms to suggest multiple structural concepts tailored to specific boundary conditions. Expanding FEM
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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within a species, going beyond the limitations of single-reference genomes. By integrating multiple genomes from different individuals or populations, pangenomes can provide a more comprehensive
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skills and be interested in developing a collaborative program of applied research in robotics. For example, this may include sensor development, applied robotic perception, algorithm development, or other