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A PhD studentship is available for commencement October 2026 – January 2027 as part of the first Cohort of a new EPSRC Centre for Doctoral Training in UK Semiconductor Industry Future Skills* led by Swansea University in partnership with the University of Leeds. The PhD studentship will be: 4...
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Primary Supervisor: Dr Ke Li Foundation models trained on DNA and RNA sequences are beginning to transform genomics, but their predictions often remain difficult to interpret. A model may identify a
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Fully Funded PhD Position: Decoding Chromosome 1 Risk in AMD Using Stem Cell–Derived Retinal Models Host: Newcastle University (UNEW), UK Consortium: MSCA Innovative Training Network Pandora Start date
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11 Jul 2026 Job Information Organisation/Company University of Amsterdam (UvA) Research Field Biological sciences » Biological engineering Biological sciences » Biology Computer science » Modelling
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2 PhD Positions in Computational Modelling of Biological Membranes and Adaptive Functional Materials
at the University of Münster invites applications for two fully funded PhD positions in computational modelling of biological and functional material. The two projects address complementary questions in biological
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-level power, thermal and energy-efficiency models for future heterogeneous computing systems built on advanced CMOS technologies What you will do Continued technology scaling and the integration
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a mixture of computational, analytical and machine learning approaches to model the heat transfer to fuels and their physical and chemical behaviour, including changes in chemistry and physical
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of the disease. A major constraint of most existing methods for cure models is the sufficient follow-up assumption, i.e. the study duration should be longer than the time span of possible events, which is rarely
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Are you interested in developing next-generation modelling tools for sustainable food production? Do you enjoy working at the interface of engineering, environmental sciences, and systems analysis
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Department of Spatial Economics The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging