36 big-data-machine-learning-phd Postdoctoral positions at SUNY University at Buffalo
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infection models, multi-omic approaches and data analysis, and/or anaerobic bacterial culture. Learn more: Our benefits , where we prioritize your well-being and success to enhance every aspect of your life
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Physiology and Biophysics Classification Title Postdoctoral Associate Department Physiology and
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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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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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or demonstrated interest in entrepreneurship, small business management, strategic decision-making, supply chain management, and\or network analysis. Ability to acquire and work with existing data sources
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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, Pharmacy Classification Title Postdoctoral Associate Department Pharmacy Posting Number P250107
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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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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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position. The successful candidate will be driving cutting-edge research into textile fiber recycling sorting technologies using spectroscopic and hyperspectral methods coupled to machine learning techniques