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Field
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full-time career. What we're looking for PhDs (in penultimate or final year) in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research
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performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior Alpha Monetization. Blend quantitative
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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
We are seeking an exceptional candidate for a fully funded PhD studentship investigating the role of sleep and circadian rhythms in elite athletic performance, co-funded by Brighton & Hove Albion
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Profiling hardware and feasibility of new
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PhD Position on socio-economic effects of climate tipping points Faculty: Faculty of Geosciences Department: Department of Sustainable Development Hours per week: 36 to 40 Application deadline
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PhD studentship: Systems pathology of the breast tumour microenvironment in obesity. Supervisor: Dr H Raza Ali Department/location: Cancer Research UK Cambridge Institute Deadline: 17 August 2025
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Minimum Qualifications Candidates must have a PhD and proven research experience in computation analyses, statistics, mathematical modeling, or engineering. Prior experience in Ophthalmology research is not
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Inflammation and Alzheimer’s disease: PhD Scholar at the University of Oxford We are pleased to invite applications for a doctoral degree in the Department of Psychiatry, in association with St
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image