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to develop a high-performance disposable analytical tool for the on-site detection of folic acid in several food matrices. This technology is based on our recently developed wireless and batteryless, near
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data analytics, business analysis and/or informatics knowledge and skills to undertake this project, with an interest in process innovation. Prior experience in analysis-related roles within sport
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and quality‑controlled, generating high‑quality serological, molecular and genomic data alongside metadata that will feed dashboards as well as catalytic and phylodynamic models. The post includes
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, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal disorders as a case study for advancing digital health in Europe. About the
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clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal disorders as a case study for advancing digital
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are safely received, triaged, processed, sequenced and quality‑controlled, generating high‑quality serological, molecular and genomic data alongside metadata that will feed dashboards as well as catalytic and
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-gradient-driven diffusiophoretic focusing for power-free analyte concentration Integrate nanomaterials and microfluidic components into scalable, user-friendly LFA prototypes Validate device performance
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Three 3.5 year PhD studentships in artificial intelligence in medicine or health data science funded by the National Institute for Health Research UCL UCLH Biomedical Research Centre are available
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available. LISS DTP trains future research leaders to tackle global challenges through interdisciplinary collaboration, data-driven approaches, and impactful research. We welcome applications in any
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on the project choice/previous experience/interests, as a PhD student, you will gain hands-on experience in Synthetic chemistry and analytical techniques (HPLC, LC–MS, NMR) Designing and synthesising compounds