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. degree in cognitive neuroscience, neural computation and machine learning, or a related field with a strong background in EEG, functional near-infrared spectroscopy (fNIRS), or computational modeling, as
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computational screening, or machine learning for materials property prediction is essential. Candidates with prior experience in developing AI models for accelerated materials discovery, optimization of material
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validation of machine learning models for the early diagnostics and risk stratification of progression risks (MAFLD/NAFLD, HCC recurrence, other complications, etc) among patients with chronic hepatitis B
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experience in one or more of the following areas: development of methods for multi-omics data integration, application of machine learning models in life science, single cell data analysis and spatial