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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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, 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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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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Recovery Research: Conduct and analyze fMRI studies investigating how different brain networks (language network and domain-general multiple demand network) support language processing in persons with
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waveguides. Perform device processing at the Kostas cleanroom, including lithography, deposition, etching, and wire bonding Device Testing and Measurement (20%): Test and benchmark the devices using time
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of computational pediatric cancer research. They will develop and support data processing and analysis tools, create new algorithms for focused research questions in bulk and single cell tumor
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including photolithography, polymer/resists coating and mixing, wet etching, chemical processing, oxygen plasma cleaning, nanoparticle-related tools, rapid prototyping (laser cutting and 3D printing), and