432 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" Postdoctoral positions in United Kingdom
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cell (myofiber) omic platform — developed by the PI — to interrogate ALS pathogenesis at an unprecedented level of resolution. By simultaneously analysing multiple data sets (MANT-ATP, methylome
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Research (OCMR, University of Oxford) and Oxford University Hospitals Department of Radiology (ORRU), focused on the development and delivery of funded clinical hyperpolarised imaging studies. You will
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you will manage your own academic research and administrative activities which involves small-scale project management, to coordinate multiple aspects of work to meet deadlines. You will adapt existing
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Martin and Professor Daniel Paulusma from Durham University and Professor Vadim Lozin from the University of Warwick. The general aim of the project is to develop algorithmic meta-classifications, which
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for this post. The successful candidate will be required to develop a personal research programme in theoretical cosmology (which may include numerical modelling and/or data analysis), interacting with faculty
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6. Desirable criteria Evidence of active collaboration with dry lab and co-development of algorithm for the prediction of epitopes. Downloading a copy of our Job Description Full details of the role
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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apply a novel single muscle cell (myofiber) omic platform — developed by the PI — to interrogate ALS pathogenesis at an unprecedented level of resolution. By simultaneously analysing multiple data sets