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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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given to the ability to assimilate third-cycle courses and study programmes at a higher education. The applicant should have documented knowledge in energy systems and machine learning technologies
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biology. The applicant should also have an interest in learning, or previous experience in, computer programming, particularly using languages such as Python. The ideal candidate is driven and a creative
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development