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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
computational biophysics/chemistry and drug design. The researcher will conduct research to forward the developments of biomolecular modeling and computer-aided drug design. The researcher will also be engaged in
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professional training Medical, dental, and pharmacy plans Healthcare and dependent care flexible spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial
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include tuition-free Part-Time Study and Employee Degree Program, heavily discounted eCornell courses and certificate programs, tuition aid for external education, and Cornell Children's Tuition Assistance
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field at the time of appointment is required. The successful applicants will be expected to have a strong statistical and computational background, research experiences showing independence and innovation
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fantastic benefits available: Health and Wellbeing: Our Inspire Programme promotes the importance of taking care of both our general health and mental health. Inspire manages the Employee Assistance Programme
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new postdoctoral fellow to integrate in a wider community of microbiologists and clinicians. The successful candidate will assist with project planning, data management, workflow design, graduate and
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(compensated by enlarging the contractual hours, and dependent on the teaching programme’s needs) This Post-Doc position is a unique opportunity to help reshaping supply chains, material innovation, and explore
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), data science, and emerging digital technologies in medical education. The Postdoctoral Scholar will work at the intersection of digital health, informatics, and education innovation, leveraging advanced
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outstanding youth innovation projects. These will span eight departments from the main campus and 16 affiliated hospitals of CMU. A Young Physician-Scientist Training Program aims to support dozens of young
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designing/programming experiments, recruiting/running participants, developing and using computational modeling approaches (Bayesian, RL, neural networks) to analyze behavioral and neuroimaging data