778 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions in United States
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translational vaccinology within a highly collaborative research network. Within this opportunity, you will be engaged in the following learning objectives: Applying machine-learning/AI platforms including
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, longitudinal follow-up, biospecimen and clinical data collection, EHR-based cohort development, physiologic data integration, machine learning analysis, and manuscript and grant development. Minimum Requirements
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, research, and public service. Purpose: The Postdoctoral Researcher will work on research projects in the area of wireless communication system design with machine learning applications. The ideal candidate
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: Engineering | Electrical and Computer Engineering The Postdoctoral Scholar will conduct cutting-edge research in the areas of wireless networks and machine learning. The scholar is expected to collaborate
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, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. We welcome and encourage applications from minorities
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Job Title Postdoctoral Research Associate Agency Texas A&M University Department Teaching, Learning And Culture (Tlac) Proposed Minimum Salary Commensurate Job Location College Station, Texas Job
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The Nuclear Technologies and National Security Directorate (NTNS) is seeking a dynamic and passionate Postdoctoral Appointee with strong background in statistics or machine learning to lead an
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within the Texas Children's Cancer Center. The project aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, gene knockout and knock-in screens will be
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License/Registration/Certification n/a Physical Requirements Some standing or walking. Sitting at computer workstation for extended periods. Repetitive motion. Lifting, pushing, or pulling of objects up
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—integrating first-principles simulations with machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive