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Zealand and leading cyber security provider CyberCX. Artificial intelligence is one of the most transformative fields in technology today. Revolutionising industries from healthcare to finance, AI is
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"Applied Artificial Intelligence" and "Computational Life Science" MSc Data Science (UL) MSc Nanoelectronic Systems (TUD) MSc Bioinformatik (UL) MSc Medizininformatik (UL) MSc Medical Informatics (UL
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SOFTWARE ENGINEERING, COMPUTER ENGINEERING, APPLIED MATHEMATICS, CIVIL ENGINEERING, ENVIRONMENTAL ENGINEERING, OR RELATED FIELDS – STREAMWATER PROJECT Bearing in mind Regulation No. 437/2020 on Research
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in Computer Engineering with research experience in Explainable Artificial Intelligence (XAI). LanguagesENGLISHLevelExcellent Additional Information Benefits The scholarship provides €1,040.98 per
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
applied research in the fields of thermo-fluid dynamics and magnetohydrodynamics in order to improve the sustainability, the energy efficiency and the safety of industrial processes. The Department
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results in their Bachelor's studies, and who pursue Master's level studies in Artificial Intelligence, broadly conceived Academic Requirements Master's students pursuing studies in Artificial Intelligence
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Scholarship code: SRS-25034 This scholarship is open to Master of Science (research) applicants. This prestigious scholarship is provided by the Australian Centre for Artificial Intelligence in
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, investigating biological and chemical changes during waste treatment processes, and evaluating the ISO30500 and environmental impact of treated waste outputs. Students will develop expertise in advanced
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that typology of the scholarship, followed or interpolated. and Requirement 2: Hold a master’s degree in Computer Engineering, Artificial Intelligence and/or Data Science, Computer Science or related field
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and Management, Production Engineering, Logistics Engineering, Computer Engineering, Systems Engineering or Artificial Intelligence, Data Science or related scientific areas. 2.3 – Preferential factors