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for characterization of CT images. Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images Performance Evaluation: Conduct
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-class S&T products for sensitive national security missions. The selected candidate will support research efforts in signal processing and analysis, with an emphasis on the development of novel algorithms
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Requisition Id 15721 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel quantum algorithms for materials simulation, with
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and
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algorithms for behavioral cue extraction and novel approaches for the modeling people interaction, with application to medical research and affective computing. Responsibilities: Write code and develop novel
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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. Specific responsibilities include, but are not limited to, the following: Develop the core tensor network algorithm for full RIXS cross-section simulations. Benchmark simulation results against ED codes
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical