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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Integration of phenotypic data with omics analysis Explore machine learning and network analysis methods Profile Essential A PhD in Bioinformatics, Computational Biology, Evolutionary Biology
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. You have a good knowledge of Python and machine learning. You have an excellent knowledge of English. Your research qualities are in line with the faculty and university research policies . You act with
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platforms involving sensors, instrumentation, and physical measurements Involvement in the design, wiring, commissioning, and troubleshooting of systems Collaborate closely with PhD students, postdocs, and
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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preferably adopt a systems-level approach and make use of high-throughput methodologies. Effective application of advanced machine learning analysis and data integration approaches, potentially through
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. Charlotte Scott and will work alongside 8 PhD students and 6 postdocs, 2 wet-lab technicians and 2 computational experts. This role involves working closely with the other members of the team on different
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regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial support for the whole length of the PhD. The applicant will be expected to seek independent