365 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" PhD positions in United Kingdom
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across disciplines, linking ecology with data-driven analysis; How to apply Interested applicants should contact Dr Weizhuo Wang (w.wang@mmu.ac.uk ) for an informal discussion. To apply you will need
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Engineering, Physics or related discipline. To apply, please contact the main supervisor, Dr Dumanli-Parry - ahugumrah.parry@manchester.ac.uk . Please include details of your current level of study, academic
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primary supervision of Dr Thomas Ouldridge. The student will develop predictive models of nucleic acid strand displacement rates to allow the rational design of complex networks of ever-increasing
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be based within the Centre for Atmospheric Science, supported by state-of-the-art laboratory infrastructure. The supervisory team, led by Dr Aristeidis Voliotis, brings extensive expertise in trace gas
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throughput ‘omics’ techniques, such as metabolomics. How to apply Interested applicants should contact Dr Adam Lightfoot for an informal discussion. To apply you will need to complete the online application
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Interested applicants should contact Dr Mohammed Al-Khalidi (M.Al-Khalidi@mmu.ac.uk ) for an informal discussion. To apply you will need to complete the online application form for a full time PhD in
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Primary supervisor - Dr Gareth Matthews Background: Atrial fibrillation (AF) is the most common sustained arrhythmia, affecting around 2 to 3% of the population and costing the NHS more than £2.2
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years (part-time) EligibilityUK, Rest of world Reference numberCRAN-0053 Supervisor 1st Supervisor: Dr Irene Carra 2nd Supervisor: Professor Peter Jarvis Entry requirements Applicants should have a first
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. You will have evidence of post-qualification research experience, research experience in the analysis of large biomedical or biobank datasets, a proven ability to code and a strong publication record
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- See advert for details Deadline: 13 April 2026 Supervisors: Dr Zhenhui Yuan and Professor Joseph Hardwicke Predictive Network Intelligence for Medical Telerobotics Research area and project description