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simulations on High Performance Computing, the ability to analyze and organize large datasets or model outputs, knowledge of Unix/Linux, and experience with commonly used software and protocols in
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer work to generate
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transduction, or protein-protein interaction. Computer skills in data and statistical analyses are required. A proven record of productivity as demonstrated by recent first author publications in leading peer
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, charitable trusts and foundations, international Universities and industry. The post holder will work as part of a recently-funded EPSRC Programme grant, undertaking research into nanotheranostics, support
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+ EDX · Fully Automated FIB Helios 5UX · FEI SEM Quanta and SEM Magellan Requirements: · Education: PhD in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. · Knowledge: Deep
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qualifications In this project, we advance an AI-driven T cell-targeting strategy based on de novo-designed peptide-MHC (pMHC) binding proteins. Using computational protein design, we create synthetic recognition
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of researchers who have transitioned or are transitioning from training environments in the physical/mathematical/computational sciences or engineering into postdoctoral work in the biological sciences, and who
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in collaboration with Texas A&M College of Engineering, Texas A&M School of Medicine and the state’s top-ranked Houston Methodist Hospital offer an innovative medical school program called ENMED
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The School of Computer Science and Informatics is seeking to appoint an individual to work on rigorous methods to address the risks of generative AI systems. The primary focus will be on techniques