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30th September 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in climate data analysis and machine learning emulation of hydrological models Apply for this job See
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. Experience in thermodynamic modelling and the use of simulation tools such as TRNSYS, EnergyPlus, Aspen, and Computational Fluid Dynamics software packages is essential. Instrumentation and experimentation
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sensing research in a coastal location. • Design and conduct physics-based hydrologic modelling and hydraulic simulation in the coastal environment. • Conduct field experiments in the coastal
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of stress intensity factor evolution at the crack tip. Concurrently, a numerical model will be developed to complement the experimental results and allow for the calculation of crack propagation rates. Work
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), funded by the Wellcome Trust and conducted in collaboration with an interdisciplinary team at Fiocruz in Brazil. They will be expected to contribute to the development and application of climate modelling
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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combined with first principles and multiscale simulation for the design of molecules, catalysts and materials, with applications in clean energy and decarbonisation AI for clinical and health research using
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application programming interfaces (APIs), through rigorous simulations and proof-of-concept (PoC) trials. This position is ideal for a researcher with a passion for solving complex problems at the intersection
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods in power grid simulations with HVDC and Wind Farms using PSCAD Undertake management
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: Key responsibiities: Development of new motor design concepts for electric motor drives Development of new multidomain simulation platform for electric motor drives Development of new fabrication