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across medicine, nursing, pharmacy, podiatry, and other health professions to design integrated, team-based care models that address prevention, education, and treatment of diabetes and its complications
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this gap by developing a machine learning-based downscaling framework that links coarse resolution (0.25°-1°) reanalysis and climate model outputs to fine-scale (∼100 m) estimates of surface melt and
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, privacy, access controls, and metadata management. Strong working knowledge of cloud-based data and analytics ecosystems and modern data architectures (e.g., data Lakehouse, medallion architecture
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, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python, or embedded software tools. Integrate controller logic with
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tailored for these missions. This PhD opportunity is fully funded as part of the ECHOES ERC project. The main objective of this doctoral research is to integrate coronagraphs with actively controllable
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closely connected with applied research and industry collaboration. FTMC provides a strong scientific base, international research networks, and the flexibility for doctoral students to develop independent
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professional disciplines, the university is well known for its learn- by-doing approach and Teacher Scholar Model. The university is noted for its scenic and historic 1,400-acre campus, which was once the winter
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models and transformer-based architectures to construct high-dimensional design spaces. These models are integrated with Deep Reinforcement Learning (DRL) for fine-tuning or end-to-end learning, enabling
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to the lack of generation inertia worsening power system stability. Control of such a complex system relies on detailed understanding and real-time modelling of the nonlinear dynamics resulting from
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fruitful data to calibrate physics-based crystal plasticity models and inform them with key parameters (e.g., variation of single-crystal elastic constants and critical resolved shear stresses with