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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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, such as computer science, neuroscience, engineering, physics, applied mathematics (or be near to completion of their PhD). Skills in computer programming (especially Python or C++ or Matlab) and
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Schemes of Service: Research Division: Infocomm Technology Employment Type: Fixed Term Project Overview We are seeking an outstanding and highly motivated Research Fellow (PhD) or Research Engineer
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Materials Design - Develop and apply machine learning and AI models (e.g., ML interatomic potentials, generative design, reinforcement learning) to predict and design materials. - Perform first-principles and
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of multi-modal datasets, including MRI/fMRI, behavioural and audio data Develop reproducible statistical and machine learning analysis pipelines Support grant writing, ethics submissions and project
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, or near completion, of a PhD in Electrical Engineering or a closely related discipline. Demonstrated expertise in power system dynamics, stability analysis, renewable energy integration, or related areas
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, such as computer science, neuroscience, engineering, physics, applied mathematics (or be near to completion of their PhD). Skills in computer programming (especially Python or C++ or Matlab) and
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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geophysical investigation, geomechanical engineering, and machine learning. The Centre for Urban Solutions is to provide leadership in developing innovative solutions and sustainable technologies for space
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record and demonstrated research leadership. We welcome applications from outstanding recent PhD graduates as well as candidates with postdoctoral experience who are seeking to establish or further develop