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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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via autophagy and lysosomal targeting in learning and memory and disease models using rodents and iPSC-derived cell cultures. These mechanisms will be investigated in both healthy conditions and
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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QUALIFICATIONS Education: PhD or Doctorate degree Medicine (MD) required Experience: No previous experience required Knowledge, Skills and Abilities: Learning Agility: Ability to learn new procedures, technologies
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development plan (IDP), conduct research studies, attend required courses/seminars, write grants, publish manuscripts, present oral presentations locally and nationally, and learn other skills necessary for a
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated expertise in
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career in research or academia. Participate in the University’s Individual Development Plan policy for postdoctoral scholars, have a PhD or equivalent terminal degree (such as MD, DVM, PsyD, PharmD, etc
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-performance computing. Additional experience in DNA biophysics, machine learning, and optimization is preferred. This job description intends to provide a representative and level of the types of duties and
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. GLW faculty draw on the fields of anthropology, economics, history, law, labor relations, political science, and sociology in their research and teaching. To learn more about the faculty in