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collaborative programme bringing together a team of leading experts in advanced electron microscopy imaging, first-principles modelling, metal halide semiconductor thin-film and device fabrication, and
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. The research requires experience in high vacuum systems, laser, molecular beams and laser desorption sources, charged particle beams and optics, velocity-map imaging detection, and the associated data processing
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period of 12 months in the first instance, with potential to extend. The project involves advanced theory for new ultrafast imaging experiments and is funded by Engineering and Physical Sciences Research
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induced pluripotent stem cells as disease models, microfluidic cell culture, assessments of: axon transport, calcium imaging and excitability. The post is primarily be based in NDCN, but there will be
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. This full-time post is initially fixed term for 12 months, with the possibility of an extension to 30 September 2027, subject to funding. The postholder will work under the supervision of Professor Johannes
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experience in genomic analyses, proteomic approaches, imaging analysis, iPS differentiation and bioinformatics would be especially welcome. The post available as a fixed-term contract for 2 years in the first
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the first instance Hours: Full Time (37.5 hours per week) THIS POST IS A READVERTISEMENT, PREVIOUS APPLICANTS NEED NOT APPLY About the role We are seeking to appoint a talented Postdoctoral Research Associate
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including conditional diffusion and flow matching models for synthesising Magnetic Resonance Imaging (MRI) and predictive analysis for Novartis Oxford collaboration for AI in medicine. The collaboration
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biophysics, and cutting-edge analytical technologies. Your expertise in optical microscopy, single molecule imaging, computational imaging and data analysis will help us further develop mass photometry and
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to