95 algorithm-"Multiple" "NTNU Norwegian University of Science and Technology" PhD research jobs
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-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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skills and be interested in developing a collaborative program of applied research in robotics. For example, this may include sensor development, applied robotic perception, algorithm development, or other
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data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations
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depending on the project and assigned research/scholarly functions, or other creative aspects. Preferred Qualifications Salary Commensurate with experience. Number of Vacancies Multiple Desired Start Date 09
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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roof” interdisciplinary clinical-research center. We specialize in Parkinson’s disease, movement disorders, Alzheimer’s disease, ALS, Traumatic Brain Injury, Multiple Sclerosis, and related diseases
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into the genomics of population structure and speciation in the Malawi cichlid genus Labeotropheus. This post will build on past work in which over 1000 samples of Labeotropheus from multiple species/populations have