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to work collaboratively across disciplinary boundaries is essential. The successful candidate must hold a relevant PhD/DPhil in information engineering, computer science, statistics or a commensurate
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/DPhil in relevant quantitative area, as well as knowledge of statistics and/or Bayesian learning, and necessary mathematical and computational skills to put these into practice. Skills in computer
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group of Dr. Mario dos Reis, as part of a BBSRC project on development of Bayesian methods to analyse large genomic datasets. We seek a highly motivated individual with relevant background in statistics
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accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory research, data presentation and statistical evaluation, as
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team and should be a self-starter with the ability to manage multiple activities, while conducting individual research and disseminating results. Experience in statistically analyzing and interpreting
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We invite applications for a full-time Postdoctoral Research Associate to work on the statistical properties of Denoising Diffusion Models (DDMs) project funded by EPSRC and led by Professor George
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We invite applications for a full-time Postdoctoral Research Associate to work on the statistical properties of Denoising Diffusion Models (DDMs) project funded by EPSRC and led by Professor George
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experienced people. You will have a PhD in a relevant area (e.g. epidemiology, economics, geography, public health, psychology, data science, applied statistics), with an excellent working knowledge of research
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An exciting opportunity has arisen for a Post-doctoral Research Fellow with the scientific expertise to undertake the integration and, statistical analysis of sleep and circadian rhythm data from
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pathways You will also have the freedom to determine your own research approaches within this broad framework. You will have or be close to the completion of a PhD in statistical/computational genomics with