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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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biopharmaceuticals. The research at CMB pushes the boundaries of biomolecular and bioinformatics research and engineering technologies. VIB.AI studies fundamental problems in biology by combining machine learning with
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in computational chemistry. Advanced programming skills
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to work independently and use creative methods and approaches 18. Knowledge of machine learning for image classification Skills Demonstrable ability to plan and manage independent research.
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setting Previous experience with clinical populations, neuroimaging or neuromodulation, or computer programming is a plus Technical skills (e.g., Python, R, Unix) are also highly desired but not required
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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application