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and journals. You will be expected to: Conduct cutting-edge research in: Multi-Agent Systems (MAS) for complex, dynamic, and uncertain environments. Multi-Agent Reinforcement Learning (MARL), including
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in physics, engineering, computer science, and mathematics is essential. Expertise in data analysis and inversion, Proven experience with geophysical, physical, or sensor data analysis, including
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the secure management and public communication of research data to enhance research outcomes and influence health system policy. Teaching and capacity building Design and deliver teaching on carbon analysis
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algorithm on Quantinuum hardware. This candidate will contribute to both theoretical development (e.g., complexity analysis and algorithm design) and practical implementation (quantum circuit prototyping and
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becomes necessary when a robotic system cannot be designed to run with full autonomy, often due to the complexity of the task or the unsuitable robot environment. The operator gives control inputs
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, engineering, mathematical physics, or related disciplines) Related Skills & Other Requirements Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and
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, mathematical physics, or related disciplines) Related Skills & Other Requirements ▪ Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm
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PhD Research Fellow in applied and computational mathematics Apply for this job See advertisement UiB - Knowledge that shapes society Through robust and close interaction with the world around us
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entrepreneurial ecosystem and/or on particular European countries. This would complement the expertise in CEENRG with cleantech innovation systems, policy evaluation, and analysis of innovation and
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communication skills. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis. Knowledge of network science and/or complexity sciences