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) conferred by start date Demonstrated experience with imaging and/or video datasets Training and experience in machine learning, computer vision, and deep learning methods Excellent English language
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), and in vivo fiber photometry (TDT). We are particularly looking for a PhD-level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and their causal link
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of the appointment. Demonstrated experience with deep learning methods or sophisticated mathematical frameworks applied to large-scale or scientific datasets. Experience working with observational seismology data (e.g
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: The candidate must have a PhD and extensive experience in modern deep neural network-based techniques. The ideal candidate should have: A PhD and a strong record of research or applied work in deep learning, with
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imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
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appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Precision mapping of vector borne diseases using deep learning & high resolution remote sensing data Faculty in Stanford
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contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will have the opportunity to engage in
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19.07.2022, Academic staff The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current focus on deep
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data
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equity. Pay Range: $81,000-85,000 Postdoctoral Scholar — Molecular Epidemiology and Integrative Multi-Omics of Cardiovascular Disease Dr. Themistocles (Tim) Assimes(link is external) , MD, PhD, FAHA