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Associate and Research Fellow level can be found here Joint Fellowships We have partnered with the Institute of Cancer Research (ICR) and the CNRS. If you are applying for one of these joint fellowships, we
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. Other Schmidt Sciences Fellowship roles, at both Research Associate and Research Fellow level can be found here Joint Fellowships We have partnered with the Institute of Cancer Research (ICR) and the CNRS
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
including Forschungszentrum Jülich in Germany, French National Centre for Scientific Research (CNRS)-Orsay in France, Oak Ridge National Lab & the University of Tennessee in the US and with industrial
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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
Python or R is preferred. Ability to analyze multi-omic data, including microbiome data, would be an advantage. Ability to build algorithms and data pipelines would be ideal. Create a Job Match for Similar
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a Research Fellow to contribute to a project focused on algorithm design in Game Theory and Fair Division. Key Responsibilities: Formulate mathematical models for research problems in computational
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing