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Field
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The successful candidate will have completed a PhD in chemistry education or related field (ABD will be considered), and will be performing research in line with the PI's research program. The postdoctoral scholar
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services that support
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, and analyze research data; keep a detailed notebook summarizing experiments and recording research data; Maintain a computer database of research data; tabulate and display data for presentation in
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to the application under CV/Resume. Required educations and experience Appropriate PhD in a related field. Preferred qualifications PhD, Computational Biology, Bioinformatics, Computer Science Training in statistics
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. . Basic Qualifications Must be a recent PhD graduate within the last three years. * Must meet educational requirements prior to employment start date. Additional Required Qualifications Experience in
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. The school’s student population is around 4000, across undergraduate, postgraduate and research programmes. Our vision is to lead business thought and practice to improve global society and well-being
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including: Medical: Multiple plan options Dental: Multiple plan options Additional Insurance: Disability, Life, Vision FMLA Medical leave Tax deferred annuity savings option plans (401k, 403B, 457) Tuition
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requirements and such other tasks that are assigned to you. Core Responsibilities: Support PhD students on their research methodologies, experimental designs, and theoretical approach. Participate actively in
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treat one another, work together, and measure success. Basic Qualifications: A PhD degree in material science, mechanical engineering, electrical engineering, robotics, or a related field completed within
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and