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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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. The successful candidate will engage in innovative research addressing statistical methodology, machine learning, and/or learning techniques in complex biomedical and health-related challenges. We particularly
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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next generation of scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML
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, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports departments in integrating active
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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artificial intelligence and machine learning Strong analytical and problem-solving skills Experience working with large administrative or clinical datasets Proven ability to work both independently and