1,775 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Central-European-University" Fellowship positions
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positively in the research activity of the NIHR Mental Health Leadership Award, focusing on children and young people, under the direction of the Mental Health Leader. Data collection and analysis, vital
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statistical data and an interest in the ways in which education can teach democratic values. The postholder will be part of a small research team based at UCL and the University of Roehampton and will play a
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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Supervise the collection and maintenance of clinical trial documentation, including data records and equipment maintenance logs Ensure compliance with clinical inventory management procedures Develop and
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collaboration, and assisting with the preparation of a competitive large scale funding application to a major external funder, including coordination of supporting documentation, budgeting information, and
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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to prove their eligibility to work in the UK. Please see: Right to work in the UK | Selwyn College For further information with the link to the application system, please click on the 'Apply' button above
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Posting Details Position Information Posting Number PG191567PD Position Number 00111652 Position Type Post Doc FLSA Departmental Information Department ID 192001 - CVM Teaching Hospital Department
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discipline (statistics, mathematics, computational biology, data science). Strong programming skills (R preferred) Statistical competence (Bayesian is advantageous) Please email the PI at ephdbsl
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766