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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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of our key research directions relevant for this position. Candidates should have (or be near to completing) a PhD in Computer Science or a related subject, or relevant experience. A high degree of
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cycles and refine deliverables accordingly. The skills, qualifications and experience required to perform the role are: A PhD in Computer Science, Civil Engineering, Data Science, Information Systems, or a
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, computation, and biophysics. They will also have the opportunity to develop independent projects after gaining adequate experience. Moreover, they will receive support if they wish to participate in career
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Partnership in collaboration with Hitachi Europe Ltd, developing engineered proteins for carbon upcycling and sustainability. The role holder will collaborate with computational and biological scientists
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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replacement) project on Limits of Symmetric Computation. The position would suit a candidate seeking to obtain a PhD at the Department. The project seeks to investigate lower bounds on symmetric computation in
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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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community of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Appointment at Research Associate level is dependent on having a PhD (or equivalent experience
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers