146 phd-position-in-data-modeling-"Prof"-"Prof" positions at UNIVERSITY OF SOUTHAMPTON
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physiological data, as well as with prior experience in participant recruitment and/or experimental testing. They will hold a PhD in the field of machine learning and prediction/decision modelling or related
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monitoring and prediction/decision modelling, while supporting data collection, analysis, and dissemination throughout the project. The lecturer will also contribute 50% FTE to the delivery of UG and PGT
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Justin Sheffield. This project aims to transform our understanding of soil moisture (SM) variability and its interactions with land-atmosphere processes. The project will use cutting-edge modelling, data
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An exciting opportunity for a skilled and motivated Data Scientist to join a growing group (AXIS, Access eXtract and Integrate Safe Data) within the Clinical Informatics Research Unit (CIRU). This
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) for further information about this position in advance of submitting your application. Applicants are required to have a PhD* or equivalent professional qualifications and experience in a relevant discipline
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statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing to the development of biomarkers and predictive models. A critical part of your
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invited to contact Dr Benjamin Cerfontaine (b.cerfontaine@soton.ac.uk ) for further information about this position in advance of submitting your application. Applicants are required to have a PhD* or
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to the development of biomarkers and predictive models. A critical part of your role will be to ensure all data and workflows are reproducible and shareable, aligning with our 'data lake to discovery' approach under
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for precision targeting of AML, an aggressive leukaemia with poor survival outcomes. Building on strong preliminary data, it combines mechanistic and translational immunology with bespoke in vivo models to define
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. The project seeks to develop mathematical models for allocation of critical resources during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them