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Field
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data modalities. AI for scientific discovery: methodological advances with potential applications across biomedical and scientific domains. We are looking for candidates with A PhD in machine learning
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platforms a plus Experience applying machine learning, artificial intelligence, and large language models to research a plus The anticipated start date is September 1, 2026. The postdoctoral position incoming
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what you bring. Do you recognize yourself in this? You have completed a PhD in data science and/or artificial intelligence. You have gained knowledge of various machine learning techniques, particularly
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master levels and advancing research about the integration of cutting-edge AI and machine learning as tools to enhance the analysis, interpretation, and scalability of Remote Sensing data. The successful
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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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License/Registration/Certification n/a Physical Requirements Some standing or walking. Sitting at computer workstation for extended periods. Repetitive motion. Lifting, pushing, or pulling of objects up
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/2026 Position Qualification Position Summary Developing and/or applying artificial intelligence, machine learning and/or data science-based methods to address cutting-edge topics, including but not
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, established track record of publications in computational microscopy, computer vision, or parallel machine learning Adaptability: A demonstrated, strong willingness to learn and bridge the gap
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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science, or related computational approaches. Candidates must have experience developing or implementing machine learning methods for large-scale data analysis, predictive modeling, or biological discovery