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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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geolocated social media data, and computational techniques from network science and machine learning. It is interdisciplinary, combining theories of healthy and accessible cities with computational data
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to compliance professionals for validation studies. Training spans advanced NLP (transformer fine-tuning), financial crime typologies, privacy-preserving machine learning, and product-oriented development. You
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that integrate multi-omics data to uncover mechanisms of disease, cellular resilience, and therapeutic response. The post holder will lead research applying large-scale machine learning and foundation models
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills
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communities. These facilities create a unique offering in higher education for our students to gain valuable practice learning experience onsite, to support local and regional NHS partners, and provide a data
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low-progression backgrounds, refugees, care-experienced learners, and those with military connections Use data and insight to evaluate impact, inform strategy, and continuously improve outreach activity
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: machine/deep learning, numerical modelling, statistics, optimisation, scientific computing • Ability to work across disciplines and collaborate with academic and industrial teams Desirable: • Experience in
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students, staff, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly
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interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning, cutting-edge radio instrumentation and digital signal processing, citizen