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DATA SCIENCE ENGINEER , McGovern Institute for Brain Research (2 openings), to tackle challenging problems at the intersection of brain science and artificial intelligence. Will join world-class neuroscientists and cognitive scientists in applying machine learning, AI, and data science skills to cutting-edge research on the brain and mind . Responsibilities include helping researchers develop large-scale neural network models of perception and cognition; translating computational algorithms into parallelized and GPU-optimized code; staying up-to-date with machine learning developments; aiding labs with the integration of machine learning into their research; providing guidance for standardization, storage, and management of large data sets; and helping transition users to new computing tools.
These positions will offer opportunities for career development and a voice in the scientific directions that are explored.
REQUIRED : advanced degree (M.Sc./Ph.D.) in machine learning or computer science; experience implementing efficient large-scale parallelization for data-processing algorithms; experience with GPU optimization in PyTorch and TensorFlow, including ability to write new GPU-based operations in both frameworks; experience training large-scale artificial neural networks across multiple GPUs; experience with large-scale neural network optimization techniques, including hyperparameter optimization; experience with high-performance cluster computing and/or cloud computing at scale; experience with software engineering and publishing, and building user-friendly interfaces; experience analyzing big data and high-speed I/O programming; familiarity with HDF5 or TFRecord; ability to optimize existing scientific computing code; willingness to work with domain scientists; commitment to and experience with open science practices; experience with data management tools that facilitate reproducible science. PREFERRED : background in neuroscience and cognitive science. Job #20196
This is a three-year appointment with the possibility of extension.
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