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Field
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: developing precise parton shower algorithms and studying their consequences in jet physics. - Develop a parton shower algorithm that is precise to the next-to-single log for ee collisions. - Extend
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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workflows into structured representations suitable for AI planning and optimization algorithms. 2) Research Leadership & Mentorship: * Abstract from the practical challenges presented by the work and
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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Paul Goldberg and will work on the EPSRC-funded project “Driving Behaviour in Multi-winner Voting” within the Algorithms and Complexity Theory research theme. The position is for the two-month period of
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of Computer Science. The post-holder will report directly to Professor Paul Goldberg and will work on the EPSRC-funded project "Driving Behaviour in Multi-winner Voting" within the Algorithms and Complexity Theory
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
engaged in SMAP algorithm heritage and NISAR-era high-resolution soil moisture development at JPL, and participate in multi-mission integration research spanning SMAP, NISAR, and ROSE-L. This opportunity
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Engineering, Chemistry, Biochemistry, or related scientific discipline Experience 1. Familiar with various cheminformatics, bioinformatics, data science, retrosynthesis algorithms for enzymes. 2. Experience in
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models. However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In