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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate predictions Ability to work in a team Ability to communicate orally in
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both institutions and industry partners. About the Project You will join FabricFlow – an innovative AI-powered ecosystem that revolutionises how fabrics are tracked and managed in the fashion industry
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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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methods. Strong collaborative and interpersonal skills, with flexibility and confidence to work across varied tasks. Excellent written, oral, and presentation skills, with ability to engage both specialist
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amenable to therapeutic targeting. This position will involve the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with
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a rapidly advancing field, as well as providing opportunities to manage and take responsibility for both research tasks and people. Informal enquiries can be made to Professor Zayats via email. This
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research and schools engagement project aiming to support the more inclusive teaching of British political history as set out in the AQA Thematic GCSE specification, Britain: Power and the People: c1170 to
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related area: emotion/ emotion regulation, stress, self-/socially-shared regulated learning ([S]SRL), affective computing Strong writing skills and ability to conduct independent research as evidenced by
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). Preferred research record in probability theory, analysis, or related areas. Ability to work independently and collaboratively in an international team. Place of work Place of employment is Aarhus University