74 phd-for-computational-mechanics-"FEMTO-ST"-"FEMTO-ST" positions at University of Cambridge
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Funder: Astra Zeneca Duration: 4 years from October 1st 2026 Supervisors: Prof Paul Midgley (University of Cambridge) and Dr Okky Putra (Astra Zeneca) Location: The studentship will be based in the Department of Materials Science and Metallurgy, University of Cambridge and the new AstraZeneca...
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Applications are invited for a fully funded 4-year PhD studentship based in the Department of Biochemistry, University of Cambridge, and the new AstraZeneca Discovery Centre in Cambridge
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technologies, bulk and single-cell RNA-sequencing, flow cytometry, multiplex immunofluorescence, and standard molecular biology and biochemistry techniques. A computational component may also be available
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At this exciting time for the College, we are seeking to appoint an experienced Programme Manager who will integrate three critical programmes of work strands, regular maintenance and refurbishment
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studies of cell dynamics and tissue mechanics during embryo development. This post contains a dual research (~2/3 time) and management (~1/3 time) role. The candidate will work closely with the PI
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PhD programme. There are currently about 80 students working on PhDs on a diverse range of topics in sociology. Further information about research interests and recent publications of staff and postdocs
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You You will have a PhD (or close to completion) in health data science, bioinformatics, computer science, computational biology, or a closely related discipline, with demonstrated experience in
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will be invited to submit two pieces of written work of no more than 10,000 words each, accompanied by a short note explaining how each fit into their overall research programme. Please note, all work
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the Department of Chemistry at the University of Cambridge to work on an ERC programme to develop new approaches to template synthesis. The appointee will join a multidisciplinary team of several post-docs and PhD
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of computational approaches to analyse and integrate single-cell and spatial multiomic datasets to unravel the effects of nucleic acid-sensing pathways (e.g. cGAS/STING, RIG-I, MDA5 and others