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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning and experimental validation to decipher the mechanism of somatic
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efficiently engineering new therapies. To do that, we use the most disruptive technologies of the last 20-years: machine learning and synthetic biology. Our team is highly interdisciplinary, including
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Experience in analysing drugs and metabolites from human breastmilk Competency in using computer software to collect and process data, e.g. use of Excel, statistical software and machine learning approaches
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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computational foundations of machine learning. There will of course be time to pursue independent research. The expectation is that the post-holder will use the project to complement their own research
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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• Ability to work well as part of a team and rapidly acquire new skills • Detailed subject knowledge (PI to describe subject knowledge required) in the area of research • Likelihood of advanced skills
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to address the unacceptable barriers faced by BAME students as they negotiate their different learning environments. You will have: - A PhD (or equivalent) in a relevant field such as liver disease, immunology