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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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The Oxford Internet Institute has an exciting opportunity to join the Governance of Emerging Technologies research programme, working under the supervision of Professor Brent Mittelstadt and
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
related field. Strong quantitative and programming skills (e.g., R required). Experience in ecological modelling with different Artificial Intelligence methodologies, including but not limited to machine
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using in vivo models. The role will also include supporting the general program of research within the pre-clinical team. You will work in Containment level 2 and 3 facilities to assist with murine
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related discipline and have begun to establish a strong research profile, evidenced by a strong, well-cited publication record. Proficient in Python, R, BASH and/or other relevant programming languages, you
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), have good organisational and communication skills and have experience running research studies in humans. Experience with data analysis and basic experience using programming languages (e.g. R, Python
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in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
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demonstrated ability to analyse and interpret complex multidimensional data. Experience of programming in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages