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animal models. This role offers a unique opportunity to contribute significantly to cutting-edge research aimed at deepening our understanding of gynecologic cancers and innovating new treatments. As a
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
and molecular bases of chronic health conditions and/or human disease. A variety of experimental approaches, encompassing in vivo, in vitro, and in silico models, will be considered. Candidates
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engine. Algorithm Development: Contribute to designing, prototyping, and testing algorithmic models for personalized content recommendations. System Evaluation: Support the evaluation of the recommendation
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a background in computer science and programming. The ideal candidate will have strong skills in web scraping, processing unstructured data (both text and images), and experience with modeling
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and Bioinformatics using Python and R and practical experience of applying these skills and techniques in Machine Learning models and software development. High level analytical capability is essential
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practices beyond Euro-American models, and reinforcing Exeter’s position as a UNESCO City of Literature and a growing hub for literary and creative industries in the South West. You will be expected
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mathematics, optimization, modeling and simulation, data science, artificial intelligence, and logistics and operations. Why RAND? - Reputation for Excellence: Be part of a non-profit, non-partisan organization
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Fellows with appropriate graduate mentors. 4) serving as a role model and resource for all of the Fellows by sharing their experiences related to the practicalities and intangibles of an academic career
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Fellows with appropriate graduate mentors. 4) serving as a role model and resource for all of the Fellows by sharing their experiences related to the practicalities and intangibles of an academic career
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supervision of a postdoctoral fellow to study breast cancer initiation and progression using a newly developed mouse model of breast cancer together with primary patient samples. You will additionally learn a