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, machine learning and AI-based computational tools to advance biomedical as well as oncology research. The fellow will work under the supervision of Dr. Veera Baladandayuthapani and there will be
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of design and fabrication of medical devices, 3D printing, microfluidics, mechanics of materials, biomaterials, blood-material interactions, computer aided design, and/or in vitro/in vivo evaluation
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Required Qualifications* A PhD in Information, Human-Computer Interaction, Computer Science, or a related field; conferred by the start date Desired Qualifications* Experience translating research outcomes
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discipline or a related field - Strong demonstrated verbal and written communication skills Desired Qualifications* - Familiarity with manufacturing systems and processes - Experience with machine learning and
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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technologies and machine learning; and interact with collaborators and team members Prepare data reports for weekly meeting with PI and bi-monthly reports for weekly lab meeting Attend educational activities
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medical, dental and vision coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Researching and developing novel machine learning architectures for integration across
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of different intervention strategies on the genesis and severity of cytokine release syndrome and other side effects resulting from innate immune activation during CAR T-cell therapy. This will involve the use
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, i.e., machine learning models explicitly constrained by physical laws (e.g., conservation of mass, momentum, or energy) or designed to integrate physics-based models and data-driven learning
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* Experience with image analysis or medical imaging Established record of peer-reviewed scientific publication Prior experience / comfort with computer programming is a plus Modes of Work Positions that