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for Predictive Product Properties (MTV)". Your research focuses on the experimental and material-modelling foundations required to enable predictive and controlled TVAM. You will be embedded in the Processing
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results but are hampered by large individual differences in response. It is evident that we need to rethink the premises of randomized controlled trials (RCTs) to better predict who will benefit from which
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outcomes, while ensuring access to reliable and affordable energy. The EE Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials
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workflows that integrate modern AI and machine learning concepts (e.g., surrogate models, adaptive sampling strategies) into the drug discovery pipeline to increase throughput and predictive accuracy
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to improve predictive models and inform design strategies. Work in Practical Settings — engage directly with NIHE to implement and test research methods in operational housing schemes. This work will equip
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with advanced analytics techniques such as predictive modelling and data mining. - Experience with artificial intelligence and machine learning applications in data analytics. - Proven leadership in
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27th April 2026 Languages English English English The Department of Structural Engineering has a vacancy for Two PhD positions in “Micromechanics-based modelling of ductile failure in high-strength
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(DERs), PV, BESS, diesel gensets, or DC microgrids is highly advantageous. Familiarity with energy management systems, microgrid control strategies, or predictive/dynamic control will be an advantage
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interdisciplinary initiative focused on advancing Predictive, Preventive, Personalized, and Participatory (P4) approaches in health and medicine. Within the IRAP framework, the project’s scientific goal is to
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of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models. Develop multistate sequence design algorithm for rational design of RNA switches. Develop database