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analysis, including statistics and machine learning techniques. Proficiency in scientific programming, especially Python and/or Matlab, and experience in shell scripting. Excellent written and oral
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abound. They include: (1) An inter-school neuro-engineering initiative among at least Neurobiology, Neurosurgery, and Biomedical Engineering with opportunities in neuromodulation, brain-machine interfaces
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large-scale multimodal neuroimaging dataset, brain
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with experience in data-intensive research, machine learning, and artificial intelligence are especially encouraged to apply. About the Department: The Department of Physics hosts active research groups
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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implantable neural interfaces, and machine-learning approaches for decoding brain activity. Outstanding candidates in all areas of biomedical engineering are encouraged to apply. Candidates must have a Ph.D. in
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engineering, including (but not limited to): Imaging and Biomedical Devices: advanced biomedical imaging technologies; neuroimaging, optical imaging; ultrasonic imaging; multimodal and hybrid imaging systems
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Neurobiology, Neurosurgery, and Biomedical Engineering with opportunities in neuromodulation, brain-machine interfaces, and molecular engineering; (2) A thriving Alzheimer’s Disease Research Center with
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demonstrable experience in the field of contemplative neuroscience and experience with developing machine learning pipelines. A Master’s degree in neuroscience, data science, computer science, or engineering is
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assigned Requirements A Ph.D. degree in Neuroimaging, Biomedical Engineering, Electrical Engineering, Physics, Computer Science, or other related disciplines, with experience or keen interest in processing