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Field
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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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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supply chain processes, including transport operations, fleet management, and operational readiness frameworks Model & Algorithm Development: Design, build and implement optimisation models for various
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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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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic
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, quantum science, condensed matter, materials, photonics and interdisciplinary applications of physical science. This role sits within a collaborative quantum science project at King’s on quantum algorithms
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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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(the final scope will be developed together with the candidate, and it is not necessary to cover all topics): Group fairness: developing and analysing algorithms and metrics for ensuring fair treatment
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the development, implementation, and testing of signal processing and imaging algorithms for high-frequency ultrasound structural and functional imaging. Support experimental setup, data collection, phantom
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development of explainable and interpretable classical and quantum deep learning algorithms - Design and development of hackathons and other collaborative methodologies to promote the control of artificial