45 proof-checking-postdoc-computer-science-logic Postdoctoral positions at Cornell University
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% Computer research 15% Field Research 7% Writing 15% Requirements Required: - PhD in Plant Biology, Microbiology, Entomology, Plant Pathology, or a related field. - Experience working with plants as part of
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, Microbiology, or related fields. Proof that all Ph.D requirements have been fulfilled before the start date is required. A successful candidate should have experience operating a triple quadrupole LC-MS system
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benefits program. Hiring Range: $56,484 - $80,000 based on Education and Experience. Join Us: This position represents a unique opportunity to advance your research career in energy systems engineering at a
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% Computer research 15% Field Research 7% Writing 15% Requirements Required: - PhD in Plant Biology, Microbiology, Entomology, Plant Pathology, or a related field. - Experience working with plants as part of
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% Computer research 15% Field Research 7% Writing 15% Requirements Required: - PhD in Plant Biology, Microbiology, Entomology, Plant Pathology, or a related field. - Experience working with plants as part of
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colleagues in Computer and Information Sciences, Economics, Engineering, Natural Resources, and other units on campus. To be considered for this position, apply at https://academicjobsonline.org/ajo/jobs/29631
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Postdoctoral Associate – Global Labor and Work, ILR Future of Work Program The Industrial and Labor Relations (ILR) School at Cornell University is seeking a Postdoctoral Associate to join the ILR
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Cornell University, CALS Molecular Biology and Genetics Position ID: Cornell -CALS Molecular Biology and Genetics -POSTDOC [#30069, WDR-00053216] Position Title: Position Location: Ithaca, New York
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. Requirements A Ph.D. in an engineering discipline. The candidate must have relevant background in at least two of the following areas: Solid mechanics, Transport phenomena, Computational modeling, Multiphase
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in the context of anthropogenic stressors. Research Context and Opportunity: The postdoc will have the opportunity to leverage many years of bat viral spillover data collected in the field and the lab