147 machine-learning "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions at Rutgers University
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analyses or the ability to effectively learn these techniques will be needed. Effective oral and written communication skills. Preferred Qualifications Experience in immunology, T cell biology, and cancer
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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Effective spoken and written English required. High level of computer literacy required. The individual must be able to navigate the highly complex and often unpredictable nature of scientific research, as
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Please send a cover letter, curriculum vitae, and the contact information (names, emails) for three references to Dr. Nicole Cain (nicole.cain@rutgers.edu) Quick Link to Posting https://jobs.rutgers.edu
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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-making. Among the key duties of this position are the following: Develop and refine computational models (e.g., mechanistic, machine learning, or hybrid approaches) for ICU patients. Integrate and analyze
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industry. The Fellowship Program provides robust learning experiences related to Medical Affairs, Commercial/Marketing, Regulatory Affairs, Clinical Development, etc. The Fellow will spend the majority
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proficient in working with large data-sets (observational or numerical), machine learning, and running/analyzing numerical simulations. The initial appointment will be for two years at Rutgers University
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limited to artificial intelligence, computing theory (algorithms, complexity), data science, statistics, discrete mathematics (graph theory, combinatorics), game theory, machine learning, optimization
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limited to artificial intelligence, computing theory (algorithms, complexity), data science, statistics, discrete mathematics (graph theory, combinatorics), game theory, machine learning, optimization