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for medicine use before and during pregnancy. This postholder would work primarily on a recently funded programme of work to develop a novel approach to understanding and communicating the Safety of Medicines in
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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for an outstanding, post-doctoral researcher with proven expertise and practical experience in relevant techniques including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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collaborative and interdisciplinary and the ability to work in a team is essential. About You The successful candidate will be expected to have a PhD degree in biological or computational sciences or equivalent
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desirable if the post holder has experience in the development of production-quality software, computational Bayesian inference, and strong communication skills. For more information see the detailed job
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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About the Role We are recruiting an enthusiastic postdoctoral research associate to conduct a scientific programme of work focussed on pain mechanisms in epidermolysis bullosa, under the supervision
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with Prof. Heath Murray at Newcastle University. The group has routine access to the Titan Krios microscopes at LonCEM and eBIC and an in-house computing infrastructure for data processing. About You We
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support projects using GWAS, Mendelian Randomisation, and polygenic risk score analysis to uncover genetic mechanisms underlying complex traits. There are opportunities to integrate omics data across