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for candidates to have the following skills and experience: Essential criteria PhD or equivalent experience in relevant area. Knowledge or interest in Natural Language Processing, ideally as applied to big
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spending risk affects savings. Knowledge of economics, programming in MATLAB and JULIA, and the Health and Retirement Study data is necessary. Understanding linkages with administrative medical records is
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specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
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specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
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) in machine learning or a closely related field you should possess sufficient specialist knowledge in the discipline to work within established research programmes and have an ability to manage own
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specialist knowledge in mechatronics design and control, and proven programming experience in Python, MATLAB or C/C++. Informal enquiries may be addressed to Professor Liang He (email: liang.he@eng.ox.ac.uk
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attached to Prof. Eric French's Montague Burton Professorship. The research aims at exploring and understanding the drivers of medical spending, and how medical spending risk affects savings. Knowledge
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expected to be bioinformatic in nature. Applicants must have a PhD in a relevant subject, experience of macrosynteny analysis and phylogenetic analysis of gene families, and a thorough knowledge of animal
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techniques in a fast-paced environment with a strong team focus. This represents a unique opportunity to acquire a strong practical knowledge base in a broad range of highly desirable transgenic biology skills
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track