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Field
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. Renowned for hands-on learning and pioneering research, Mines educates future leaders in STEM fields who will make a meaningful impact on the world. Our vibrant community of supportive faculty, tenacious
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, deep learning, and data analytics will be beneficial. 4. Experience in Dynamo programming would be preferred. Willing to learn and responsible. 5. The appointed candidates will support the planning
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for recording across multiple cortical/ striatal circuits •Optogenetic and electrical real-time perturbations, including interventions directly related to clinical deep brain stimulation. •Parametric
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functional data analysis, tensor regression, high-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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with computer-aided design software. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and
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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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circuits that regulate motivational and emotional states. The lab uses many state-of-the-art techniques, including deep-brain calcium imaging (2-photon in vivo microscopy) with single-cell resolution and