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profiles using energy modelling tools • Build thermo-fluid dynamic models of HVAC and district cooling networks • Propose improved system architectures and network efficiency strategies • Design and validate
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polymer materials. Working at the intersection of polymer mechanics and materials design, the group develops polymer networks capable of operating under extreme loading and environmental conditions. The
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research fellow to work on the development of Physics-informed neural networks (PINNs
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mangroves peatlands, and streams, as nature based solutions. The lab integrates field-based experiments, high-frequency sensor networks, stable isotope approaches, and modelling to study water, carbon
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, including deep neural networks and physics-informed neural networks, to analyse large datasets from gyrokinetic and fluid simulations of plasma turbulence Develop and train reduced-order models that capture
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for accurate localization and tracking of 5G network User Equipment (UE) in urban environments. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Study 5G protocol and implementation
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courses, events, capacity-building, and networking activities. The successful applicant will also assist in organising conferences and seminars, contribute towards the programme’s networking activities and
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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spatiotemporal systems by combining physics-driven baselines with data-driven correctors. Formulate and solve inverse problems using Physics-Informed Neural Networks and relevant methodologies. Conduct rigorous
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strong network of contacts in the region. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU