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Privacy, (iv) Analysis of Academic Collaborations, (v) Human-Bot interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD in one of the following: Data Science
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: Required Qualifications PhD in Biology or a related field At least one first-author primary research article in a peer-reviewed journal Proficiency with standard molecular, cell, developmental biology, and
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education and economic development needs. Federally designated as a senior military college, one of the university's signature leadership programs is its 800-member Corps of Cadets on UNG's Dahlonega Campus
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key objective is to hire a recently conferred PhD with outstanding qualifications and core values of high standards of excellence in innovative research. Benefits at UTA We are proud to offer a
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Qualifications: PhD in English. Relevant teaching experience Responsibilities: As part of your teaching assignment as a Part-time Instructor, your duties will include the following: Developing and/or updating a
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Intelligence (BMIHAI) is searching for a highly motivated PhD, Masters, or undergraduate student with training and interest in biomedical informatics and health AI to build and maintain a web-page for the BMIHAI
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Status Full Time Posting Number 25FA0890 Posting Open Date 09/24/2025 Posting Close Date 11/17/2025 Qualifications Minimum Education and Experience PhD in Art History or a closely related field required by
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Status Full Time Posting Number 25FA0890 Posting Open Date 09/24/2025 Posting Close Date 11/01/2025 Qualifications Minimum Education and Experience PhD in Art History or a closely related field required by
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professionals at undergraduate and graduate levels, promotes lifelong learning, and enhances the well-being of individuals, children, and families residing in rural, urban, and military communities throughout
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operation, aligned with financial and operational incentives. The ideal candidate will have: A PhD in Computer Science or a related field Experience in developing and evaluating reinforcement learning systems