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project led by Professor Kam Bhui and Dr Roisin Mooney in Oxford. The project investigates methods to improve postpartum outcomes of severe mental illnesses in ethnically diverse mothers (POSIE) with
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understanding of dark energy. Projects may span a broad range of topics, including improving Type Ia supernova modelling and standardization, developing and applying advanced data analysis and statistical methods
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of comparative genomics and molecular evolution analyses to identify these targets. The project will make use of software developed in the Kelly group as well as other widely used software for biological sequence
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understanding under challenging conditions. The work spans core methods, research and system-level deployment, with application domains including logistics, agriculture, social care, and inspection. About You You
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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Council (EPSRC) UK. Find out more about the Kirrander research and group here . About you Applicants must hold a PhD in Physics, Chemistry, or a relevant subject area or be close to completion, prior
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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
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urgent challenges in major depression. The successful candidate will have formal mentoring and gain experience at the interface of academia, healthcare, and industry, contributing to discoveries that shape
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related dementias later in life. You will hold a relevant PhD/DPhil (or be close to completion) in the field of mechanical or biomedical engineering, applied mathematics, or another field relevant
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will have the opportunity to teach. Applicants should hold a PhD/DPhil, (or close to completion) in atmospheric physics or related fields. Experience in atmospheric physics and aatmospheric remote