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Project Part B in Trimester 1, 2026 Master of Computer Science - semester 2, 2025 enrolment in: COMP SCI 7100A - Research Project Master Computer Science Part A Masters of Mathematical Sciences - semester 2
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or Leipzig University. AI is viewed as an interdisciplinary undertaking that requires talents in computer science, engineering, mathematics, social science, law, the natural sciences, and application areas
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, such as used in Banner Finance/HR, TOAD and Excel software. Ability to create queries, produce reports, and summarize results for analysis. - Ability to understand and interpret complex regulations, such as
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from developing and emerging countries. It offers the opportunity to continue their academic and professional career in innovation-driving STEM fields in Germany with a Master’s degree in mathematics
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a related field, please describe and highlight your experience doing language-focused/linguistic analysis, such as discourse analysis, in your motivation letter and CV. You have a strong academic
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offering solutions to complex problems and creating new possibilities. At La Trobe, our students gain essential skills in programming, data analysis, and machine learning, equipping them to shape the future
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Overview Eine Druckversion dieser Ausschreibung (PDF) steht Ihnen in den weiteren Registerkarten (z.B. „Bewerbungsvoraussetzungen“) zur Verfügung. A print version of this announcement (PDF) is available in the further tabs (e.g. “Application requirements”). Objective The programme aims at...
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researchers from previous Hort Innovation funded projects. A comprehensive gap analysis of papaya phytophthora management will be followed by development of high-throughput method to quantify soil fungal load
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the Digital Systems and Intelligent Sensors group (DSIS). within the School of Electrical Engineering, Computing and Mathematical Sciences. DSIS endeavours to utilise technology to assist people with
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available in the further tabs (e.g. “Application requirements”). Programme Description The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with