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Field
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ecology, remote sensing, and computer science. UAV imagery and increasingly sophisticated and targeted AI algorithms can estimate forage quality, biodiversity, and the abundance of individual plant species
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-age-gap prediction algorithms applicable to Asian populations by integrating large-scale plasma proteomic datasets generated using the Olink and SomaScan platforms. The organ age gap is defined as the
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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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for real-world deployment. Key Responsibilities: Develop algorithms for DAS signal processing, wavefield analysis, feature extraction, and interpretation across infrastructure monitoring, urban geophysics
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monitoring including geohazard detection such as sinkhole and subsidence. Key Responsibilities: Develop algorithms for passive seismology, seismic noise analysis, geophysical imaging, and seismic source
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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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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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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, 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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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic