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Field
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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physiology Coding proficiency (e.g., Python, R) and familiarity with deep learning tools are strong assets A strong publication record, critical thinking, and collaborative mindset Application Instructions
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: Proficiency in Python and major deep learning frameworks such as PyTorch or TensorFlow Familiarity with transformer architectures and large language models (e.g., BERT, GPT) Experience in building, training
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radiation therapy treatments. At least one position will be offered to a researcher that has experience in deep learning and AI development and a willingness to apply these approaches in radiation therapy
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.) during medical imaging and radiation therapy treatments. At least one position will be offered to a researcher that has experience in deep learning and AI development and a willingness to apply these
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structural biology to tackle challenging scientific questions. Your responsibilities will include, but are not limited to: Multi-omics analysis of bulk and single-cell sequencing data. Developing deep learning
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in signal representation/processing, esp for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state
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research, especially deep learning literature, and how these methods apply to our use cases Ability to manage multiple projects and assignments with a high level of autonomy and accountability for results
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Responsibilities: To conduct independent research in deep learning theory. To produce publications in top conferences and journals. To offer guidance and assistance to any students involved in the project
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 14 hours ago
.) Departmental Preferred Experience, Skills, Training/Education: Ph.D. in design-related discipline, specializing in deep learning and biometrics. A strong background with evidence of experimental and AI/machine