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experiences that developed or applied at least one of the following techniques to solve a problem related to the broad application areas as listed above: signal processing/time series analysis, machine learning
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electroencephalographic (EEG) signals, which capture the brain's neuroelectrical activities. The research will employ both conventional biosignal processing techniques and AI/machine learning methods to characterize
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individuals with a strong background in AI, machine learning, and deep learning, who are passionate about tackling current health research challenges. Essential qualifications include: A solid understanding of
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: · A doctoral degree or equivalent in an appropriate field (e.g., neuroscience, psychology, computer science, machine learning, or engineering). Excellent scientific writing ability and strong
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variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and can demonstrate real-world application of these techniques. ADDITIONAL JOB DETAILS: The
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. Maintains records, files and logs of work performed in laboratory notebooks and computer databases. Compiles data and records results of studies for publications, grants and seminar presentations. Employees
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(MRI, fMRI) with rhesus macaques and humans, with the goal of better understanding the cognitive and neural mechanisms of learning, memory and decision making. The ideal candidate should be motivated
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. This collaborative work may include helping to support audio/visual production for the school. KEY RESPONSIBILITIES: Maintains technologies that support the teaching and learning mission of the University. Deploys
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models and experience with modern LLM models and algorithms. Proven experience in successfully developing and deploying machine learning models in a production environment, with a focus on scalability and
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, Computer Science or another quantitative field. Strong problem-solving and critical thinking skills. Knowledge of real world application of machine learning techniques (clustering, decision tree learning, artificial