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be offered a fixed term contract for 1 year. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD or equivalent
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. About You The successful applicant will have, or soon obtain, a PhD degree in mathematics or related, or equivalent level of professional qualifications and experience, with expertise in at least one of
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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, emissions, and productivity. Decision-Support & MCDA Implement a machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
of patient care, education, and research. We strive to promote faculty, staff, and learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning
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Purdue’s strategic focus on health equity and population health. Program Goals and Learning Objectives The fellow will gain experience in: Designing and conducting pharmacoepidemiologic studies in cancer and
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-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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mentoring of graduate students. The required qualifications are: PhD degree in Civil Engineering, Materials Science, Chemical Engineering, or related field Extensive research experience related to concrete
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human