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Field
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FLOW research group is a young, dynamic group working in the fields of thermodynamics, fluid mechanics, and data-driven modelling. At the Department of engineering Technology (INDI) — Thermo and Fluid
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, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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(3) years.Supervisor:Dr Mohamed Lamine Faycal BELLAREDJ, Assistant ProfessorDepartment of electrical engineering, Universite de Moncton (Moncton campus)Email: [mohamed.lamine.faycal.bellaredj
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renewable energy, AI-driven engineering, and industrial research. Cranfield’s expertise in wind energy systems, predictive maintenance, and AI applications provides an ideal environment for cutting-edge
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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conduct world-leading research in the development of microwave-based technologies for medical diagnostics, treatment, and monitoring. Our research activities span computational modeling, algorithm
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Contract: Full Time/Fixed Term for three (3) years.Supervisor:Dr Mohamed Lamine Faycal BELLAREDJ, Assistant ProfessorDepartment of electrical engineering, Universite de Moncton (Moncton campus)Email