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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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particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and
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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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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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in science, technology, engineering, or mathematics. Proven experience in machine learning, exemplified through published research results, is required. The selected candidate will have excellent