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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot
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close collaboration with a deep-tech startup. You will work in an internationally recognized research environment with access to state-of-the-art cleanroom facilities and collaborate with leading academic
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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biology to characterize carcinogen DNA damage and molecular signatures in the oral mucosa of smokeless tobacco users. This unique project will build on our deep understanding of tobacco-induced cancer
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learning and deep learning techniques to the biological sciences. The ideal candidate will have expertise in artificial intelligence, with a specific focus on deep learning applications in structural biology
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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, normalizing flows, VAEs, generative transformers, or related methods. Strong programming skills and experience with modern deep learning frameworks. Experience with large-scale model training, distributed
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research Experience with machine learning, deep learning, or multimodal data analysis Experience conducting human-subject research and IRB-compliant studies Experience working with healthcare systems
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implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic pathway prediction. Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful