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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 7 hours ago
to the agency as part of NDA/BLA submissions. You will have access to unique research and training opportunities, ability to interact with top regulatory scientists and use state-of-the-art techniques. Learning
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mentorship. Develop, implement, train, and validate machine learning and deep learning models for AI-driven prediction of cell physiology, metabolism, and functional behavior, with input from the research team
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emerging technologies, transportation data, policy, research and all modes of transportation across the Department. As a Fellow, you will learn to facilitate the transformation of our transportation system
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Schemes of Service: Research Division: Infocomm Technology Employment Type: Fixed Term As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads
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will participate in grant and fellowship review, mentor graduate students and help collaborate on other events and projects at the Institute. The fellow may be invited to teach a Harvard class during the
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at the Institute. The fellow may be invited to teach a Harvard class during the course of their appointment. Basic Qualifications Candidates must have received their PhD no later than February 2027, and must have
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well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify
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-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel algorithms for: Fine-grained video understanding Concept learning Temporal
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for full Stokes vector detection. The candidate will focus on optical simulation, cleanroom nanofabrication, device integration, optoelectronic testing, and machine learning-driven signal reconstruction