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Field
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. Job Requirements PhD or equivalent research experience in Quantum Computing, Theoretical Physics, Applied Mathematics, or a closely related field; Strong foundation in quantum algorithms, particularly
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economics Develop state-of-the-art algorithms in algorithmic game theory and fair division Design and conduct experiments to evaluate the algorithm performance Job Requirements: PhD degree in computer science
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noise, allowing only specific algorithms with relatively shallow quantum circuits to be executed. In the NISQ era, hybrid algorithms run partially on quantum computers and partially on classical computers
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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the COVID-19 vaccines) is a highly dynamic and fast moving field. We have developed a generative AI algorithm to optimize the mRNA, and we are looking for an experienced wetlab researcher to test the
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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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of machine learning approaches, and uncertainty quantification in ML algorithms. The ATLAS group has four staff members, in addition to two PhD students and one postdoctoral researcher. For this project we
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and planning algorithm for high-speed autonomous vehicle. The work will involve algorithm development, simulation, test rig set-up, and experimental validation. Requirements: The candidate must at least
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UiO/Anders Lien 15th August 2025 Languages English English English PhD Research Fellow in Machine Learning Apply for this job See advertisement About the position Position as PhD Research Fellow in