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engaging hands-on activities and assignments, students will learn to identify and utilize various information and computer system components and peripherals. They will gain proficiency in using the world
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or machine learning 4) A strong interest and motivation in elucidating functional mechanisms through the use of quantum beam techniques * Assigned department Existing departments [Work location] * Address 466
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contribution to society activity. Teaching responsibilities Graduate level: One or more courses related to the applicant’s specialized fields and Project Based Learning courses from those offered in the master's
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Integration) Course, and Information Creative Course. Students will study information literacy, data science, programming, databases, machine learning/deep learning, and application development. The curriculum
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of the recruitment and description of the project Electrical Engineering (electrical machines, control, plasma, electric power system, new energy, power electronics, high voltage) [Work content and job description
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. The Architecture Course aims to cultivate professionals capable of designing, constructing, and managing excellent buildings and housing by learning architectural technologies, such as design, structure, and
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position) Designing a machine-learning-based bias correction method using retrospective forecasts and reanalysis data for comparative calibration. Topic 3: Development of seasonal prediction models (one–two
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; identification of novel phases of matter through machine learning; and the development of new algorithms for the simulation of quantum matter. Applications from strong candidates with complementary interests
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significant results by developing rich applications across diverse fields in conjunction with the advancement of modern AI and machine learning. We believe that the theory and methodology of data science are
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KEK, QUP Position ID: KEK -QUP -ASSOCIATEPROFESSOR6 [#30166, KEK-QUP-AP2025-1] Position Title: Position Location: Tsukuba, Ibaraki 305-0801, Japan [map ] Subject Areas: Data Science / Machine