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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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candidate will hold a PhD in physics, biophysics, physical chemistry, engineering, or a related area, or have submitted a PhD thesis prior to taking up the appointment. The research requires strong interest
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the group. The planned investigations are primarily experimental in nature, but will proceed in close conjunction with insight from theory and simulations. The ideal candidate will hold a PhD in physics
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biological questions about how cytoskeletal proteins are used by disease-relevant organisms. We have access to excellent facilities such as the Central Oxford Structural and Molecular Imaging centre (COSMIC
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creativity in this endeavour, together with the appropriate skills and knowledge, required to work with Dr. Johnson and collaborators to deliver the research aims. These include (1) imaging altermagnetic
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cytoskeletal proteins are used by disease-relevant organisms. We have access to excellent facilities such as the Central Oxford Structural and Molecular Imaging centre (COSMIC), as well as the Micron imaging
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the Neurogenesis and Brain Cancer group led by Prof. Simona Parrinello. The team uses a variety of state-of-the-art technologies, including advanced imaging, single cell and spatial ‘omics’, barcoding, mass
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practical workshops, and we recently partnered with KCL’s Spatial Biology Facility , an advanced centre equipped for high-resolution spatial transcriptomics and multiplex imaging, to turn large-scale data
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug
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provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake management/administration arising from research