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-adherence to asthma medicines. Evidence synthesis: To develop "programme theories" based on implementation science mechanisms on how hospital services can deliver behavioural interventions. Co-design: Working
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, and experience of working at the interface between fundamental research and therapeutic innovation. Project description Project title: “RIBO-LINC: Linking data-driven solutions and RNA innovation
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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language Have knowledge of algorithm design and common data structures It is merit if the candidate has: Any knowledge of biology Experience of Rust Experience of R and Python Experience of machine learning
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Objectives The PhD candidate will be involved in: Design and synthesis of novel bi- and tridentate CAAC ligands Exploration of coordination chemistry with first-row transition metals (Mn, Fe, Co, Ni). Full
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, biological and nanoscience domains. The candidate will be expected to develop their own research project compatible with the project vision, design and execute experiments, analyse and interpret data, and
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Clinical Researcher in Paediatric Leukaemia to join the Childhood Cancer and Blood Disorders Group, to contribute to initiatives that advance research and innovation in paediatric leukaemia. Main
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hold a Bachelor’s or Master's degree in computer science, chemistry, pharmacy, biomedical sciences, physics or a related field, with a focus on drug design computational chemistry. - You have experience
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research project Optimal adaptive space-time boundary and finite element methods. The project focuses on the design, numerical analysis, and implementation of novel numerical algorithms to efficiently solve
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intervention manuals, protocols, or stakeholder engagement strategies; d) Experience in experimental or quasi-experimental research designs in the field of mental health promotion; e) Participation as a