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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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Offer Description The successful candidate will be expected to work primarily on aspects related to precision predictions for the LHC and parton-shower simulations. The project encompasses the development
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will be developed. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also
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inform our understanding of mental disorders through the study of variation in their neural realization. We aim to translate our computational findings to develop improved diagnoses and personalized
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, integrated circuit designers, and quantum algorithm developers Analyze and interpret experimental data, contributing to scientific publications, patents, and presentations. Engage with the wider international
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distribution (partitioning) to achieve the highest efficiency while considering the merits and constraints. The successful candidate will develop software tools for distributed quantum algorithms, circuits, and
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); execute PoCs and tech transfer with foundries, equipment/materials/metrology vendors. Data & Platforms: Establish robust data governance and MLOps pipelines; develop reusable algorithms and prototype
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. The position is offered within the newly established AGATE Centre for Algorithmic Game Theory in Socioeconomics. Further career development at Charles University will be supported. Informal inquiries are welcome
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title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01