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learning, and implementation on mobile edge devices such as smartphones and tablets for estimating clinical scores from patient videos. In parallel, the candidate will contribute to the development of
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/1qx5sh5sxjki1ivmnqvbr/JHM_PDA_092826.pdf?rlkey=tjei3tmocexxesccofble867f&st=og3o855s&dl=0 REQUIRED : PhD in a field of quantitative science; strong background in machine learning and signal processing; experience with
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collaboration is particularly relevant. Computer Science and HCI : PhD in Computer Science, Human-Computer Interaction, Information Science, or a related field, with expertise in natural language processing
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health, social and clinical psychology, environmental health, genetics and epigenetics, biostatistics, natural language processing, and machine learning. Primary Research Activities (70%). · General
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health, social and clinical psychology, environmental health, genetics and epigenetics, biostatistics, natural language processing, and machine learning. Primary Research Activities (70%). · General
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, such as Abaqus, including user-defined material subroutines Ability to program in Python and develop automated simulation, data-processing, and inverse-identification workflows Familiarity with
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staff at MIT. REQUIRED : PhD in engineering that includes domain-specific expertise in biomanufacturing (e.g. fill-finish, drug substance, downstream processing, automation); teaching experience in
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processing raw data for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB , R, or Stata); Writing papers for management and economics
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datasets, including data processing, quality control, visualization, and integration with dietary and clinical outcomes. Analyze and interpret study results and lead the preparation of first-author
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scientists, pathologists, and clinicians, and will take intellectual ownership of projects from data processing through biological interpretation and publication. Required Skills Required PhD (or