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opportunity employer and seeks candidates who understand, respect, and can contribute to the University’s mission and values. Visit the Department web page for further information (http://www.villanova.edu
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Qualifications: A PhD in Physics, Astrophysics, Data Science or a closely related discipline is required. Strong proficiency with programming, especially in python and optionally in C/C++. Strict adherence to open
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Computer Science, Artificial Intelligence, Data Science or a closely related field Experience with instructional technology Preferred Qualifications: PhD or other terminal degree preferred Physical Requirements and
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industry experience. Demonstrated commitment to teaching excellence and innovation. Excellent communication and interpersonal skills are required. Preferred Qualifications: PhD in Chemical Engineering or a
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online settings Master’s degree in Business Administration, Entrepreneurship, or a related field required Experience with instructional technology Preferred Qualifications: PhD or other terminal degree
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30 Scholars (15 per annual cohort) from around the nation who are PhD students through mid-career scientists. The first cohort will run from June 2026 to May 2027, and the second will run from June
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. Excellent computer skill, command of Microsoft Office Suite, and the ability to learn new computer programs. The individual must have a deep commitment to the well-being of the Villanova University, a
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experience. Preferred Qualifications: PhD or terminal degree. Physical Requirements and/or Unusual Work Hours: Special Message to Applicants: For full consideration for the position, complete applications must
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maintains student and faculty data. Supports student and faculty retention and serves on search committees as needed. Standard workload consistent with the FCN workload policy, compromising credit hours
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of this project. Participate in weekly meetings and help to prepare reports and presentations for project sponsor. Minimum Qualifications: A PhD in Mechanical Engineering required; successful PhD thesis defense