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interactions Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job Requirements: Master qualification degree in ecology, biogeochemistry, Earth/soil science
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cases, data requirements, model outputs, and deployment workflows for the medical device platform. - Design and implement reliable data acquisition pipelines from medical device hardware, sensors, imaging
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and data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research
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algorithms and experimental validation platforms for high-precision, high-speed and robust three-dimensional sensing. Key Responsibilities: Conduct research on structured-light three-dimensional imaging
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-powered diagnostic algorithms, and integration with digital health platforms for real-time monitoring and clinical decision support. WITEC brings together interdisciplinary researchers from MIT and
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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long
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develop flexible and soft electronics for integration into textiles, wearables, and electronic skin, including tactile sensors, actuation, and haptic devices. • Advance digital knitting, weaving
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analysis, algorithm development, simulation, and hardware-in-the-loop experimentation. The Research Fellow will work closely with the Principal Investigator and collaborators/students across NTU Singapore
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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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efficient navigation algorithms for multirotor operations around vessels. The role will focus on integrating drone airspace-usage predictions with Vessel Protected Volume models, developing optimisation and