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. You will contribute to Technical Area 2 (Respiratory Risk Assessment), developing and applying quantitative health-risk and epidemiological models that link indoor exposures to health outcomes using
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applying quantitative health-risk and epidemiological models that link indoor exposures to health outcomes using measures such as Disability-Adjusted Life Years (DALYs). Working with built-environment
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), developing and validating models that quantify infection risk in buildings using airflow and pollutant transport modelling. This role focuses on linking building performance, ventilation design, and pathogen
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years and in the relevant areas of Machine Learning / Artificial Intelligence, Credit Risk Modeling and Operations Optimization Modeling; The candidate must have strong programming skills in Python, and
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teams, and of leading others through mentoring, role modelling and excellent communication skills. What we offer NCTU is based in the School of Medicine at the University of Nottingham, has close links
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We are seeking a highly motivated and skilled Research Associate/Fellow to join an innovative translational research programme focused on childhood brain cancer. Based at the University
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specific tissue models. The post will be based within the School of Life Sciences with periods of secondment to Prof Shrike Zhang’s Laboratory in Harvard University, USA. The ideal candidate is highly
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multipartner cluster, supporting researchers by adapting microfluidic platforms to a range of specific tissue models. The post will be based within the School of Life Sciences with periods of secondment to Prof
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microfluidic platforms to a range of specific tissue models. The post will be based within the School of Life Sciences with periods of secondment to Prof Shrike Zhang’s Laboratory in Harvard University, USA. The
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and industry coordination. The postdoc will contribute to empirical research, scholarly publications, and the design of human-AI collaboration models. Work will be based at the University of Nottingham