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structure to the vessel wall. A key focus of the project is polycystin-1, encoded by the PKD1 gene. PKD1 is best known for its role in polycystic kidney disease, but emerging evidence suggests that it also
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-funded project, subject to contract negotiations. You will develop and apply machine-learning and structural-bioinformatics methods for protein design, with a particular focus on modern generative
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, and to study population structure and (adaptive) differentiation along elevational gradients. You will have the opportunity to generate new genome assemblies for white butterflies that are only found
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for this post you should; • A PhD (or close to completion) in Statistical Genetics, Genetic Epidemiology, Computational Biology, Bioinformatics, Statistics, Computer Science, Applied Mathematics, or a
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al. Nature Genetics 2020, Costea et al. and Schoeberl et al., Mol Cell 2023, Mol Cell 2025). For a list of ongoing projects and publications, please visit: https://www.kcl.ac.uk/research/pavri-group
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these approaches with methods for learning explicit, interpretable mechanistic ODEs, including their symbolic structure [3]. Lastly, recent work from the team includes nonparametric mixed-effect ODE models
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evolution in Miscanthus hybrids, and to investigate how regulatory, epigenetic, and structural mechanisms contribute to the balance or dominance among subgenomes. Miscanthus is a notable bioenergy crop
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directly underpin the development and evaluation of machine learning models for genomic anomaly detection. The role is primarily bioinformatic and genomic in nature; experience in AI and machine learning is
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will have a degree in life sciences, bioinformatics, data science, health informatics, or a related discipline. Experience coordinating and integrating scientific, clinical, or research datasets and
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and construction materials by replacing fossil-derived carbon with biogenic and captured carbon feedstocks. The post holder will join the Microbial Biotechnology & Bioprocessing group as part of