390 proof-checking-postdoc-computer-science-logic positions at University of Texas at Dallas
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years in corporate/business experience. Preferred Education and Experience Preferred Qualifications Excellent written and verbal communication, including outstanding presentation skills and computer
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Salary Range Commensurate with experience up to $43,502/yr Pay Basis Monthly Position Status Regular full-time Location Richardson Position End Date (if temporary) 05/31/2026 Posting Open Date 04/23/2025
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Salary Range Commensurate with experience up to $43,502/yr Pay Basis Monthly Position Status Regular full-time Location Richardson Position End Date (if temporary) 05/31/2026 Posting Open Date 04/23/2025
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Work Agreement is required upon employment. Use of personal computer and other standard office equipment may be required. Must be located within the State of Texas (or Must be located within the DFW Area
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Holidays All UT Dallas employees have access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. About
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scientific methods that foster these skills. Our training program enables middle school through ninth grade teachers to take advantage of this important brain development stage and optimize student learning
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. Skilled use of all equipment normally required for use in a student health facility. General computer skills, CPR, and AED trained. Preferred Education and Experience Prior training or certification in
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Posting Details Posting Details Posting Number S06330P Position Title Research Associate Functional Title Postdoctoral Researcher Department Mechanical Engineering Salary Range $55,000 Pay Basis
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Summary The Boyd Computational Social Science Lab is seeking a highly motivated post-doctoral scientist who is passionate about exploring the intersection of computational methods (e.g., machine learning
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Summary The Boyd Computational Social Science Lab is seeking a highly motivated post-doctoral scientist who is passionate about exploring the intersection of computational methods (e.g., machine learning