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Intelligence and Machine Learning. Join a team of scientists at the leading macromolecular crystallography beamlines and at the computing center and contribute to science projects at the interface between AI
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and developing a machine perfusion system to improve organ preservation. The candidate will work in a dynamic, multidisciplinary environment alongside PhD-level engineers and scientists, graduate
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years of experience post receiving their PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural language processing
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related discipline, with a focus on security, privacy, or applied machine learning, and with less than 5 years post receipt of PhD. Demonstrated research experience in at least one of the lab’s research
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the group's core research areas, and a proven ability to conduct independent, high-impact research. Experience in cybersecurity for cyber-physical systems, digital twins, BIM, AI and machine learning
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-physical systems, digital twins, BIM, AI and machine learning, robotics, or digital construction technologies is highly desirable. Strong programming and analytical skills, excellent written and verbal
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crystal / thin film scattering measurements, exploiting developments in artificial intelligence and machine learning. We also invite candidates with interests in beamline automation and autonomy
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://sandrasiby.github.io/ . The lab website can be found at https://sites.google.com/nyu.edu/haven-lab The successful candidate will engage in research that includes applied machine learning, systems building, and Internet
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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Humanities Scholars Program Postdoctoral Associates Call for Applications: Humanities Scholars Program Postdoctoral Associates Open to Cornell PhD Candidates and Recent Cornell PhDs Eligible