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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
and machine learning, and for the public to see the worlds of the outer solar as they would appear to our eyes for the first time. The envisaged project includes: image selection, cleaning and
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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data. Building on these results and codebases, the successful candidate will work on a bioinformatics and machine learning research project on the inference of alternative splice forms using deep
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feature filtering procedure to deal with the large feature set necessary to predict the thermoelectric ZT of a material. - Improve the already existing experimental dataset. - Apply different machine
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 2 months ago
disseminate the developed methods. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09574 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Bioinformatics
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physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi