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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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analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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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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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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Station, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives