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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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associate will also provide leadership in coordinating different projects and advising more junior lab members. The current and prior work of the lab include deep learning algorithms for detection
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computational and data analytical methodology development and implementation; experience in supervised and unsupervised machine learning, low-dimensional models or deep learning models, and willingness to learn
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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
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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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. · Publish manuscripts reporting the project’s progress and innovations. Applicants must have a PhD by the position start date. The applicant should be an expert in Python programming and deep learning APIs
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developing and applying advanced statistical models, machine learning, and deep learning approaches. As such, we seek applicants with strong quantitative backgrounds in remote sensing and time series analysis