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Field
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scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising data, energy, and processing resources while adapting to the different computational
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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The Opportunity: The Department of Electrical and Computer Engineering in the College of Engineering and Computer Science is seeking a Post Doctoral Scholar to support the UCF Center of Ethics and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how
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this project, we will develop new algorithms and computational schemes as well as further develop existing computational frameworks in the team. We will focus on two related frameworks in the project
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6 Mar 2026 Job Information Organisation/Company IFM/Linköping University Research Field Physics » Computational physics Researcher Profile Established Researcher (R3) Application Deadline 30 Mar
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's
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: genetics, epigenetics, inflammation, metabolic pathology, autoinflammatory pathology, autoimmunity, arthritis, computational analysis, mathematical modeling, applied algorithms, machine learning in biology