35 big-data-and-machine-learning-phd Postdoctoral positions at SUNY University at Buffalo
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Bioinformatics and/or Cheminformatics. Experience working in computational drug discovery, particularly multiscale applications. Experience working in Python and Bash. Understanding of machine/deep learning topics
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Pharmacy Classification Title Postdoctoral Associate Department Pharmacy Posting Number P250107
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or disability status. Minimum Qualifications Doctoral degree (PhD) or equivalent from an international university in areas related to Artificial Intelligence and/or Data Science All degree requirements including
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machine learning algorithm to improve the modeled surface meltwater in the Goddard Earth Observing (GEOS) model. Advocating and adapting the model based on collaborator feedback is key to the success
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate Classification Title Postdoctoral Associate Department Biological Sciences Posting Number R250057
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Physics Classification Title Postdoctoral Associate Department Physics Posting Number R250045
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applications from candidates in Computer Science and Engineering, with a focus on a broad range of research specializations, including: Trustworthy AI and machine learning and its societal impacts Cybersecurity
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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experimental background with a desire to learn computational techniques. Job Duties will included: Model development, model testing, and manipulating large data sets Data generation and hypothesis testing May