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Field
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skills. Excellent programming skills in Python and Julia with experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Experience building complex software systems, preferably with industry
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Laboratory (TNEL) in the University of Minnesota Department of Psychiatry has an NIH-funded opening for a post-PhD scholar at the intersection of neuroscience, brain stimulation, and behavior. Our laboratory
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problem solving strategies used in nature and to ground these ideas by fostering deep collaborations with experimental biologists. Most recently, we have been interested in neural circuit computation and
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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with a team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Experience in machine learning/deep learning methods
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of funding proposals. Qualifications: A PhD degree in Materials Science and Engineering, Metallurgical Engineering, Materials Engineering or closely related field is required. The applicant should have
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analytics - Proficiency in Python, deep learning frameworks (e.g., PyTorch, TensorFlow), and large-scale data analysis Additional Application Materials Required Cover letter CV Research Statement or Relevant
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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the brain. We are particularly looking for a PhD level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and its causal link with specific neural circuits
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it is not required that the candidate possess a deep theoretical understanding of AI, practical proficiency in using AI will be considered in the selection process. Applicants must hold a PhD prior to