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Field
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contact with participants after they have taken part in the research. Support the development and submission of funding bids including: working on data and impact plans, networking with non-academic
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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frameworks and pipelines Familiarity with single-cell multi-omic data integration and network or pathway inference tools Experience working in high-performance computing or cloud environments Interest in
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novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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immunocytochemistry, electrophysiology and live cells imaging. The aim of the projects is to approximate cellular phenotypes in an in vitro model of Bipolar Disorder (BD), and attributing abnormal network activity
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provision including flexible working, caring support (including a Parenting and Carers Fund and the Carer’s Career Development Fund), training, and a variety of diversity and inclusion networks. Staff can
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conducting calibration observations with the new receiver. Additionally, you will get to participate in a new VLBI program where full Stokes observations at millimeter wavelengths are conducted. Your network
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closely with Dr Zsófia Boda on the ERC Starting Grant project: “Applied stereotypes, social networks and self-fulfilling prophecies: How stereotypes reinforce social inequalities”. You will take a leading