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. Previous experience with machine learning applications in molecular modelling, including experience with at least three of the following Python libraries: TensorFlow, PyTorch, JAX, RDKit. Previous
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automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen
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Proficiency in written and spoken English, with strong communication and collaboration skills Preferred qualifications Experience with machine learning or statistical modeling Familiarity with high-performance
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 19 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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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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algorithms and routines for image processing, image reconstruction and enhancement, deep learning model training and inference, explainability/visualization, and statistical analysis of AI performance. Conduct
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23 Jan 2026 Job Information Organisation/Company Rīga Stradiņš University Research Field Medical sciences » Health sciences Computer science » Modelling tools Researcher Profile First Stage
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design next-generation computer architectures for running large AI models on embedded and edge systems under strict timing, energy, and memory constraints. You’ll explore hardware-aware optimization and co
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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Scientist will perform routine and complex mathematical modeling, machine learning, AI, computational, and statistical procedures to answer a variety of questions focused on direct clinical applications