577 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "CNRS" positions at Cornell University
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computational methods, proficiency in R or other applicable software packages, ability to develop scripts for R and Echoview, and statistical modeling. Interest in fisheries, fisheries acoustics, aquatic ecology
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research program and peer-reviewed publications that apply advanced data science, statistical methodology, or statistical theory to advance the mission of the department. Teaching (50%) – The successful
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. Supervision Exercised The job will require weekly meetings with the PI and regular presentations a lab meetings. No supervision required. To apply: Please apply via Academic Jobs Online https
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should be submitted to Academic Jobs Online at the following link: https://academicjobsonline.org/ajo/jobs/31193 For full consideration, please include the following materials in PDF format with your
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the “Ithaca is Gorges” lifestyle. The University seeks to meet the needs of dual career couples and has a Dual Career program to assist with dual career searches. For more information, go to: https
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-supported program) and the Macromolecular Diffraction Facility of the Cornell High-Energy Synchrotron Source (MacCHESS, an NIH-supported National Resource) and will involve collaborative projects and beamline
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initiatives. For more information click here . Application Procedure: Interested parties should submit a resume and cover letter describing qualifications on-line at https://hr.cornell.edu/jobs under staff
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January 2, 2026. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/30767 . Qualified candidates should submit a short cover letter, curriculum vitae, and contact
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, limnology or related fields. Strong quantitative background: ability to deal with large datasets using computational methods, proficiency in R or other applicable software packages, ability to develop scripts
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, particularly of non-model organisms Computer programming and experience with the solution of numerical problems, machine vision, and analysis of next-generation sequencing data High-throughput screening