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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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across scales ranging from single bacteria, single host cells, 3D in vitro models to infected hosts. We have developed new imaging technologies to visualise the interface between the host and the pathogen
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About Us Applications are invited for a clinical research fellow in Cardiac MRI to undertake clinical and research focussed on advanced cardiovascular magnetic resonance imaging under
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Applications are invited for the role of Clinical Research Fellow within the Academic Unit, Mental Health and Clinical Neurosciences, based in F3, in the Magnetic Resonance and Precision Imaging (MR
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of imaging protocols (MRI, MRS, OPM-MEG). Candidates will benefit from a demonstrable experience in these fields. The core abilities and attributes required include resilience, creative problem-solving
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impact alongside academic and industrial partners. You will be responsible for: Design, prototype, and validate embedded control systems for advanced BMS solutions, using microcontrollers (e.g., Arduino
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internationally recognised for its research in craniofacial biomechanics. Located in UCL Mechanical Engineering and supported by state-of-the-art imaging and material characterisation facilities, the lab focuses
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machine learning, and for precision-aware scheduling in distributed systems. They will design, develop and refine a software prototype system for distributed serving of machine learning models that leverage