227 parallel-and-distributed-computing-phd Fellowship positions at Nanyang Technological University
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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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reports and presentations for meetings, progress reports and conferences Any other tasks as requested by the Investigator Job Requirements: PhD in engineering or relevant discipline Demonstrated strong
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updates to principal investigator and funding agency Report writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning
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Performing CO2 adsorption and mixed-gas separation performances Job Requirements: PhD from a reputable university in the field of chemistry, chemical engineering, materials science or other related disciplines
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: PhD in the field of Polymer Chemistry. Ability to work independently and as part of a team with strong initiatives. Good communication and interpersonal skills. Good synthetic experimental skills
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+ VR for Education curriculum To organize AI + VR for Education activities Job Requirements: PhD degree from a reputed university with an interdisciplinary nature Has experience on AI and VR development
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forward the use of phase field models in earthquake rupture dynamics and fluid-driven fracture processes. The project bridges applied geophysics and computational mechanics, and is jointly developed with
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy