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Professor. Candidates should have: A PhD in English linguistics or literature by the start of the appointment, a record of publications, preferably in leading journals, and demonstrated capacity to obtain
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Posting Title Graduate PhD Student Intern (Summer) – Mathematical Optimization . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per Week 40 . Working at NLR NLR is located
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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researchers, to undertake your own innovative research in and across the fields of robotics, electrical power and signal processing, machine learning and AI within the School of Electrical Engineering and
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, typically gained through completion of an undergraduate degree in a related field. General computer skills and ability to quickly learn and master computer programs. Ability to work under deadlines with
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, typically gained through completion of an undergraduate degree in a related field. General computer skills and ability to quickly learn and master computer programs. Ability to work under deadlines with
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study in mathematics, statistics, machine learning, or science that will establish eligibility for PhD study. Applications close on 28 November each year. For more information and to apply visit
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools