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Field
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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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one of the following areas: wireless localization, wireless sensing, AI/machine learning for communications, or signal processing. Ability to conduct experimental research independently and
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Schemes of Service: Research Division: Infocomm Technology Employment Type: Fixed Term As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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Technology and is closely connected to the Birkbeck Centre for Creative AI and the Birkbeck Immersive Learning Centre. Together these centres bring expertise in art history, museum studies, creative AI
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Computer Science, Artificial Intelligence, Mathematics, Engineering, or a related field. Entry level candidates with demonstrated expertise in artificial intelligence (AI), machine learning, deep learning
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with vessel protected volume estimates to identify safety-buffer overlaps, developing multi-agent path-planning, and machine-learning methods for corridor allocation, airspace capacity optimisation, and
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an industry partner. Experience with research software, data pipelines, and simulations, machine learning, high-performance computing, CANFAR, or advanced data systems. Evidence of mentoring or supervising
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particular emphasis on integrating satellite LiDAR and UAV data with field observations. Applying statistical modelling, automated machine learning approaches, and artificial intelligence for the analysis and
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Engineering, Computer Engineering, HealthTech, MedTech, Product Development, Clinical Engineering or related disciplines with relevant experience in engineering, prototyping, product development or healthcare