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engineering, computer science, statistics or a commensurate discipline with specialisation in machine learning. Acquire sufficient specialist knowledge in machine learning to work within established research
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engineering, computer science, statistics or a commensurate discipline with specialisation in machine learning. Acquire sufficient specialist knowledge in machine learning to work within established research
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Applications are invited for a Medical Statistician to join our growing Trial Statistics team in the Primary Care Clinical Trials Unit. The successful applicant will be expected to work closely and
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adversarial and/or distributional robustness; probabilistic/statistical verification and certification; (multi-agent) reinforcement learning and stochastic control; Bayesian methods and probabilistic circuits
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researchers currently using the resource. To be considered for the role you will be educated to a relevant PhD/DPhil (or be close to completion), in epidemiology, statistics or a related subject. Proficiency in
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with IDDO statisticians and clinicians to certify the data is in the format required for statistical analyses. It is essential that you hold an undergraduate qualification in a scientific or heath
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partners across all aspects of data capture, processing and analysis. To be successful in this role, you will hold a Masters level degree in Statistics, Computing, or other numerate/related subject together
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We have an exciting opportunity for a Postdoctoral Health Data Scientist to join the research group led by Associate Professor Sara Khalid at the Centre for Statistics in Medicine, the Botnar
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. Experience in MS data analysis and statistics (i.e. MaxQuant, Perseus, and Prism) is desirable. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and
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). You will have a responsible nature with a methodical and careful approach to working in the laboratory independently. Experience in MS data analysis and statistics (i.e. MaxQuant, Perseus, and Prism) is