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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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relevant field, including statistics, mathematics, computer science, epidemiology. Strong mathematical and quantitative skills. Experience in the implementation of mathematical or statistical models and
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innovation sectors. The Department of Computing and Mathematics, within the Faculty of Science and Engineering, is a dynamic and research-active community comprising over 80 academic staff and 2,000 students
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: Engage with clinicians and patients in a collaborative co-design process to develop and test (using health psychology theory and methods) innovative, evidence- and theory-based tools, including: (i
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University of Sheffield, School of Mathematical and Physical Sciences Position ID: MPS -TT_IRF [#26555] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Sheffield
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, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
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; Chemistry; Computer Science; Ecology; Engineering; Environmental Sciences; Mathematics/Mathematical Sciences; Medicine; Natural Sciences; Physics; Psychology; Veterinary Sciences. This Fellowship is intended
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The Institute for Data and AI (IDAI) promotes excellence in Data Engineering, Data Science and AI theory and practice, ensuring their co-evolution and competent adoption across disciplines to enable
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adaptive trials, stepped wedge trials and cluster trials. You will have good knowledge of applied statistics and statistical theory, especially for pragmatic trials and complex randomisation systems. You
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) in one or more of the following areas: Quantum machine learning, Quantum algorithms, Quantum information theory or Theoretical Physics Essential criteria: Proficiency in at least one programming