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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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Effective and Efficient Visual Presentation of Machine Learning Outputs Derived from High-Dimensional Data to Clinicians (S3.5-SMP-Alix) School of Medicine and Population Health PhD Research Project
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applying machine learning to a large and diverse, curated clinical dataset. The candidate should have a PhD or MSc in a relevant field such as Neuroscience, Cardiovascular Science, Computer
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framework that compares and blends complementary paradigms of physics informed machine learning (such as PINNs, ODIL)—to (i) super-resolve experimental data, (ii) infer unknown parameters such as the
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, Psychology, or a related field, to be awarded before March 1st, 2026. Essential skills include an ability to code (e.g., Python, R) and interpret data, knowledge of machine learning and statistics, and a
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PhD in Computer Science / AI / Machine Learning / NLP or a closely related area) or equivalent qualifications. Extensive experience and scholarship within subject specialism. Ability to design, deliver
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effectiveness and safety. This PhD project aims to address this challenge through biomimetic engineering design, combining predictive in silico modelling with machine-learning techniques and microfluidic
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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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Development and Validation of a Multimodal Wearable Headband for Objective Bruxism Monitoring Using Machine Learning (S3.5-DEN-Boissonade) School of Clinical Dentistry PhD Research Project
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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting