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Field
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Simulation group to apply classical Molecular Dynamics and Machine Learning approaches for development of a new class of hybrid polyphenol-lipid nanoparticles with tuneable internal structure and exploration
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sampling missions design of machine learning systems for real-time obstacle detection, terrain analysis, and environmental adaptation in extreme environments implementation of multi-constraint optimisation
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modelling and machine learning to join and lead a dynamic international team of early-career researchers. This exciting role is part of a cutting-edge project investigating the structural integrity
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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. Demonstrated skills in longitudinal modelling and data synthesis, including machine learning, regression and GLM. Demonstrated ability to undertake high quality academic research in the field of dementia
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. Proficiency in deploying and managing wildlife camera‑trap networks and processing large image datasets. Experience developing and validating machine‑learning and AI models for image object detection and
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, cluster randomised controlled trials implementation science, data linkage, data science, machine learning and artificial intelligence. In this role, you will have the opportunity to engage in a series of
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of Psychological Sciences. In this exciting role, you will contribute to clinical trials and research projects focused on improving the mental health of adults with neurological conditions (e.g., epilepsy, multiple
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Control” (DP250101137). The Postdoctoral Research Fellow is expected to undertake research on control theory and machine learning techniques for project DP250101137. The Postdoctoral Research Fellow will