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available1Company/InstituteINSTITUTE OF COMPUTER SCIENCECountryPolandCityOpolePostal Code45-052StreetOleska 48Geofield Contact City Opole Website https://ii.wmfi.uni.opole.pl/ Street Oleska 48 Postal Code 45-052
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intelligence, computer algebra, computational logic and automatic reasoning Experience with SAT, SMT, QBF, MaxSAT Experience with algorithmic methods for commutative and noncommutative polynomials Experience in
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methods, focusing on their ability to solve hard problems more efficiently. Finally, selected developed techniques will be proposed for integration into real-world computer vision workflows, generating
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computer engineering or related fields; • Knowledge of Extended Reality application development and/or knowledge of machine learning, information visualization, and data analysis algorithms and methods
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English into text using court reporting methods, a steno machine, Realtime technology, software and a laptop computer. Key Responsibilities Provides interpreting services primarily for instructional classes
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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programme Reference Number AE2025-0593 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0593
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Foundation. The position will suit researchers interested in developing state-of-the-art methods in economics to develop our understanding of current and future environmental impacts of artificial intelligence
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interdisciplinary team of engineers, computer scientists, and life scientists Present your work at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and