23 molecular-dynamics-postdoc Postdoctoral positions at University of Cambridge in Uk
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to understanding the origins and progression of paediatric brain tumours and developing new therapeutic strategies. The lab combines genetic engineering, molecular biology, and translational research to investigate
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, BRCA2, and PALB2. Through advanced single cell genomics, in vivo modelling, and immune profiling, the team will study early molecular and cellular changes that occur in high-risk breast tissue. The team
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robots. They will be working with a team composed of PhD students, Research Assistants and Postdocs that is developing novel multi-robot architectures for practical, real-world settings. Current solutions
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to Research Associate (Grade 7) upon the award of PhD. The cellular dynamics of the plant hormones underpin all aspects of plant development and environmental responses. Targeted perturbations of phytohormones
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Limit of tenure applies We are seeking a highly motivated and skilled Postdoctoral Researcher in Human Physiology and Metabolism to join our dynamic research team at the Institute of Metabolic
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postdoctoral researchers in synthetic organic chemistry in the Department of Chemistry at the University of Cambridge. The successful candidate will join the dynamic and collaborative research group of Professor
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and recent publications of staff and postdocs can be found on the Department's website: http://www.sociology.cam.ac.uk The post is fixed term from 1st October 2025 for 24 months (please note that the
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the lab. This work will explore the molecular mechanisms of DNA damage responses and mutagenesis, and how sensitivity and resistance arise in different cancer cells and genetic backgrounds in response
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modelling of the C. elegans neural network. The lab also uses Two Electrode Voltage Clamp (TEVC) electrophysiology and molecular biology techniques to characterise receptors. There are a broad range of
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hundreds of samples from multiple independent marine transmissible cancer clones. The role provides an exciting opportunity to combine single-cell cancer genomics with molecular cytogenetics and statistical