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to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories and to develop approaches to predict and monitor
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International travel may be required for this role. Background This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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with colleagues from a wide range of backgrounds and areas of expertise Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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in the area of scientific computing and Computational Fluid Dynamics. Prior Experience in turbulence modelling, machine learning or the Lattice Boltzmann method is an advantage. Operational skills
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provide a creative, nurturing campus environment where our students can become the best individuals possible, learn from the best and brightest faculty, and make a positive difference in the community
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that the self-driving vehicle cannot handle. The research work on teleoperated vehicles with a focus on vehicle dynamics is about research on human and machine interaction. The work also deals with control
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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien