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, deep learning, and data analytics will be beneficial. 4. Experience in Dynamo programming would be preferred. Willing to learn and responsible. 5. The appointed candidates will support the planning
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen
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Qualifications: Experience with aging populations or neurodegenerative diseases Familiarity with deep learning and advanced statistical approaches to neuroimaging data Prior publications in relevant areas Required
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molecular dynamics and path integral simulation methods, machine learning techniques, and electronic structure techniques. Additional background in statistical mechanics and deep eutectic solvents is highly
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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Title: Postdoctoral Research Associate - Machine Learning & Advanced Manufacturing Employee Classification: Postdoctoral Research Assoc Campus: University of North Texas Division: UNT-Provost
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activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural
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in research and development of sustainable energy conversion technologies. We are recognized as global leaders in this field, supported by state-of-the-art facilities and deep expertise. Our
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: Automated tracking of ankle muscle fascicle kinematics in both superficial and deep muscles will allow for the intuitive and coordinated control of powered prostheses following leg amputations. In