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Field
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in hosting Institute visitors and assist in making IQSE sponsored activities successful. Qualifications PhD in Physics A well-qualified candidate for this position will also possess: Interdisciplinary
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/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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-month, non-tenure track, appointment. Required Qualifications Earned PhD, ScD or DrPH in public health, epidemiology, biostatistics, statistics, mathematics, data sciences, or computer sciences, or a
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: • PhD in Geography (Remote Sensing, Geomatics), Computer Science, Agricultural Sciences • Skills and/or knowledge in artificial intelligence (Machine Learning) and programming: proficiency in Python
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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related field Demonstrated experience in interdisciplinary research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong
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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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presentation/publication of research findings. Candidates with a Biology and Biomedical Science related Master's degree or DVM degree in addition to a PhD are preferred. This position will require attention
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tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier