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Strong skills in simulation methodologies Excellent communication and interpersonal skills Desirable Criteria: Familiarity with machine learning algorithms and artificial intelligence as applied
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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, organization, and function; models of perception, cognition, learning, and behavior; and statistical and machine-learning approaches for understanding neural data and brain function. We are particularly
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 16 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and
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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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above) grades. You have a strong background in deep learning. Previous experience with robotics, world models, reinforcement learning or other ML-based techniques for robot control is considered a plus
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gliomas. The project integrates generative AI, interpretable models, uncertainty estimation, and federated learning to improve clinical decision-making, data privacy, and personalized medicine
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
of proficiency in either R or Python in the areas of machine learning, deep learning, statistical analysis, computer vision, and/or graph analysis Experience with data engineering to create data