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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
experience with remote sensing data, specifically LiDAR (e.g., GEDI), Synthetic Aperture Radar (SAR), and multispectral optical time-series. Experience exploring machine learning and deep learning
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foundation models or foundation models for structured data is particularly relevant to this position. Key qualifications include: Strong research experience in deep learning and foundation models
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computational postdoctoral fellow to lead core deep-learning work across surgical computer vision, multimodal fusion, and clinical translation. Project overview You will advance funded work that
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validating deep-learning and machine-learning models using echocardiography, cardiac CT, ECG, portable ultrasound, and multimodal clinical data. Building scalable pipelines for image ingestion, DICOM/PACS
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machine learning and deep learning methods (e.g., CNNs, LSTMs, transformer architectures) applied to biological data. ● A track record of independent or co-led research projects and first-author
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Intelligence 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
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a plus. Strong knowledge of and experience in machine learning and deep learning techniques, and relevant libraries such as scikit-learn, PyTorch, transformers, LangChain, etc. Familiarity with
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algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems. The project focuses on the intersection of deep reinforcement learning
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infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure
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approaches for drug design by combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038