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Applications to the Runway Startup Postdoc Program open on October 15 and close on February 15. Recently completed your PhD and want to harness your deep tech expertise to start a company? Want to
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strategies. Duties and Responsibilities Design, implement, and evaluate deep learning models for spatiotemporal data, with an emphasis on medium-scale foundation models. Leverage model embeddings in causal
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 12 hours ago
carbon-cycle modeling. The project will build a unified modeling framework that uses GEDI LiDAR and Landsat/HLS data to train deep learning models capable of predicting forest structure variables such as
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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sciences Strong background in deep learning, with experience in probabilistic models (e.g., Variational Autoencoders, Bayesian approaches) Proficient Python programming for machine learning and scientific
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approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad
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in deep learning, artificial intelligence, and machine learning methodologies (Preferred) Familiarity with Python programming (Preferred). We regret that only shortlisted candidates will be notified
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values of impact, safety, respect, integrity, and teamwork Preferred Qualifications Deep understanding of AI/ML concepts, including transformers, latent-space representations, generative models, and