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Traces (ALT) lab at the Department of Psychological and Quantitative Foundations has an open Postdoctoral Scholar position for an individual with expertise in computational and quantitative methods
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will contribute to an NSF-funded project exploring a new semantic foundation for type classes and type families in Haskell. Their work will include formalizing the new approach in Lean, implementing it
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research facilities, and high-performance computing resources. Education Requirement: - MBBS, MBBCh, MS, MD, PhD, or MD/PhD in Radiology, Medical Physics, Biomedical Engineering, Computer Science, or a
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statistical skills. 6. Facility working with analysis software. Desirable Qualifications: Computer programing in Matlab, Python, C/C++ or similar. Expertise in machine learning methods and applications
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collaborative research environment and will work closely with investigators across psychiatry, neuroscience, engineering, data science, and neuroimaging methods. The position provides opportunities to collaborate
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electromagnetic geophysics methods and geophysical field data collection. Participate in field campaigns, including data acquisition and processing. Assist with laboratory setup and instrumentation. Support class
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: PhD in Sustainability, Geography, Earth or Environmental Sciences, Engineering, Applied Mathematics, Public Policy and Administration, or a closely related field, with degree conferred by the position
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learning opportunities to those seeking to support the needs of talented learners Research and Acceleration: engage in applied and collaborative research that expands methods of talent discovery and
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(such as language, memory, or attention). Work will be performed using a combination of EEG, intracranial recordings (DBS, sEEG), TMS, fMRI, EMG, brain lesions, computational modeling, and other methods
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. The postdoctoral scholar will contribute to an NSF-funded project exploring a new semantic foundation for type classes and type families in Haskell. Their work will include formalizing the new approach in Lean