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related to the programme. You will be required to work flexible hours to accommodate occasional early starts or weekend events. Main duties and responsibilities Collaborate with the wider Maker{Futures
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Dynamic skewness in longitudinal data models School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Miguel Juarez Application Deadline: Applications accepted all year round Details Panel (longitudinal) data enables learning the dynamics and relations of (groups of)...
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A search for pharmacological inhibitors of a cancer-associated adhesion GPCR in the zebrafish embryo
are seeking a motivated student with interests in developmental biology, disease modelling and drug discovery. This interdisciplinary project combines both wet bench work and computational work (bioinformatics
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ideas for improving your performance. Coordinate team teaching, which will include liaison with other academic staff and/or postgraduate assistants, to ensure that courses are delivered and assessed
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project will combine mathematical modeling and quantitative analysis of experimental data from collaborations with the Siegert group at the Institute of Science and Technology Austria, experts in high
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., Goossens, S. and Berx, G. (2025). Development and validation of a high-throughput screening pipeline of compound libraries to target EMT. Cell Death and Differentiation. doi: 10.1038/s41418-025-01515-6
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changes in channel trends and audience behavior. Oversee the creation of high-quality, accessible content that meets the needs of a diverse Sheffield student population. Lead or contribute to crisis and
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campaigns including programmed screening or Bayesian optimisation. You will characterise the resulting materials, in terms of their properties and performance for an intended application. Sustainability will
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plumbing, as well as conducting water hygiene/treatment works As a Water Compliance Plumber, you will play a key role in ensuring the safe and compliant operation of water systems across our campus buildings
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. These samplers perform gradient-informed random walks while enforcing feasibility at every step. These take advantage of recent advances and contribute to convex nonsmooth optimisation and numerical analysis