74 proof-checking-postdoc-computer-science-logic Postdoctoral positions at Cornell University
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applicant will be experienced in bacterial genetics and molecular biology techniques and have a desire to participate in a collaborative research program with frequent opportunities for mentorship and public
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collaborative research efforts. 5% Professional Development. Requirements PhD Degree in computational biology, bioinformatics, computer science, electrical engineering, or a related field. 3+ years
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Position Description Position Description: The Ezra Systems Post-Doctoral positions in the Systems Engineering Program at Cornell University spend one to three years at the Ithaca Cornell Campus
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Debanjan Chowdhury. The Postdoctoral Associate will contribute to a research program focused on driven quantum systems and their applications to quantum information science, particularly in superconducting
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offers a unique opportunity to work at the forefront of computational transportation science, AI-enabled mobility modeling, urban analytics, and cloud-based decision-support platforms for real-world
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. Desired Qualifications: Experience developing reproducible workflows (e.g., coding scripts compatible with the program R). Experience related to using participatory science and/or opportunistic data sources
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Postdoctoral Associate - Natural Resources and Environment The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and Cornell University’s second largest college
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Postdoctoral Associate - EEB - Angrawal Lab The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and Cornell University’s second largest college. We work across
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-of-the-art analytical instrumentation and computational resources. Required Qualifications: A PhD in microbiology, microbial ecology, molecular biology, biochemistry, chemical biology or any relevant fields
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. Desired Qualifications: Experience developing reproducible workflows (e.g., coding scripts compatible with the program R). Experience related to using participatory science and/or opportunistic data sources