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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
, reasoning and problem solving skills. Ability to analyze and interpret statistical data and to communicate data in a clear, concise manner. Computer literacy including the ability to use a variety of software
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location for this position is in-person on campus at Princeton University. Applications must be submitted online at https://puwebp.princeton.edu/AcadHire/position/38081. Applications should include a cover
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted online. To be considered for this position
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. Preferred Qualifications: Experience in decision analysis and developing computer-based simulations to model either infectious or non-infectious diseases. Evidence of research productivity in mathematical
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position for the 2026-2027 year. Renewal is contingent on satisfactory performance and continued funding. The aim of the program is to promote a group of promising scholars in the broad area of comparative
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doctoral degree in a related field. Interested applicants must apply online at https://puwebp.princeton.edu/AcadHire/position/39241 and submit a cover letter, curriculum vitae, contact information for three
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undergraduate and graduate trainees as appropriate in the lab and field. This position will be funded by USDA NIFA Agricultural Microbiome Program. The individual will need to have the ability to drive to field
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-doctoral program (https://postdocs.stanford.edu/ ). Required Qualifications: PhD, ScD, MD, DO, MD/PhD, or equivalent doctoral degree completed by appointment start date Degree in clinical field (nursing
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transit as well as Gaia/LSST discoveries. Indiana University also provides excellent research computing resources (high-performance computing clusters, large-scale storage, and advanced visualization