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Research Associate to join the Northern Net Zero Impact Accelerator project titled ECO-HAVEN: Energy Conservation for Households using Adaptive Edge Learning. This project develops a low-cost, privacy
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the MovAnt research group (Prof. Sebastiaan Dalle), the Laboratory of Experimental Medicine and Pediatrics (Prof. Annelies Van Eyck) and the laboratory of Physiopharmacology (Prof. Pieter-Jan Guns). This PhD
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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methodology to better understand the safety and performance risks. Finally, multiscale simulations will be used to map learnings from laboratory-based systems (up to10 kW) to predict the behaviour and
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PhD programme within QMUL’s Wolfson Institute of Public Health, under the supervision of Dr Giuliano Russo (WIPH) and Prof. Pietro Panzarasa (School of Business and Management). As part of the project
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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4-year D.Phil. studentship Supervisors: Dr Simone Falco, Prof Daniel Eakins The ability to simulate initiation and detonation effects within energetic materials is a significant capability gap
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weather prediction using Machine Learning approach (hybrid forecast). The app is also expected to be equipped with seasonal forecast for agricultural planning. You will co-design the short-, medium-, and
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Primary supervisor - Prof Kate Kemsley Join us to research and develop advanced analytical methods for tackling food fraud head-on! Economically motivated adulteration of foods is a significant
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four