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Field
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-objective optimization, or declarative problem modeling Prior involvement in open-source or reproducible systems research Interest in interdisciplinary applications of data systems (e.g., urban analytics
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at Texas A&M University has openings for multiple non-tenure track, 9-month, visiting faculty positions beginning Fall 2026. Our Visiting Assistant Professor positions are three-year appointments and carry a
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders
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learning and AI methods are preferred Strong skills in R and/or Python. An interest in conceiving and designing new projects, in line with the groups’ research focuses. A proven track record showing
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determinants of health, behavior, and outcomes. The program is supported by an NCI T32 award. Program objectives include cultivating successful, independent cancer research leaders from diverse population groups
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stereotaxic surgeries Basic knowledge of statistics and behavioral analyses/animal tracking Strong publication history psychostimulant-related research is preferred. Physical Demands Salary Range $55,000
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Expertise in quantitative modeling, computational and/or Bayesian methods Expertise using at least one programming languages in the analysis of scientific data such as R, Python, Matlab, or Julia. Expertise
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to Applicants : Please attach a CV and a brief statement of research experience and interests in the Supporting Documents section of the application in a PDF format. Please note that the applicant tracking system
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Management and Research Team Collaboration - Attend project team meetings to provide updates, report on progress, and align assigned tasks with research timelines and objectives; assist project management
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department's objectives. PRIMARY JOB RESPONSIBILITIES Conducting research on the epidemiology of suicide/self-harm and related mental health issues. Contributing to the development and implementation of suicide