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. The QML-CVC team (https://qml.cvc.uab.es/ ) is part of the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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, computer science, machine learning, or natural language processing, focusing on AI for Social Good or similar. Excellent written and spoken English is required, since the project is carried out in an international
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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comprehensive and competitive medical and dental care programs, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu
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in this position is contingent upon adequate grant funds. Position Status Full Time Posting Number 26FA0741 Posting Open Date Posting Close Date Qualifications Minimum Education and Experience A PhD in
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data