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from multiple disciplines and institutions. Required: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong background in machine learning / computer
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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of military Service members with extremity amputations. Why should I apply? Under the guidance of mentor(s), you will gain hands-on experience to complement your education and support your academic and
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balance of supervised investigation and work experience in a learning environment that will expose the participant to activities across the drug development process. We are seeking scientists from U.S
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transcriptomic data, that will be integrated with clinical metadata and whole-genome data for developing machine learning models to identify and predict patient factors driving toxicity response and sensitivity
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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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pathology on computational, molecular, cellular, preclinical and translational levels. A spectrum of scientific methods includes state-of-the-art multi-omics approaches, machine learning and implementation
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. Candidates should either hold a PhD in Computer Science, Information Technology, or a closely related field OR hold a PhD in any field in combination with strong computer programming and data visualization
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recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service. Saint Louis University, dedicated to student learning, research, health
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neuroimaging and fluid biomarkers, (b) systems biology analysis of pathways from multi-omics data using multi-layered network approaches, © machine learning for identification of genetic risk factors in ADRD, (d