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the Department of Materials Science and Engineering within the Faculty of Engineering. Project title: Machine Learning for In Situ Materials Characterisation. We are seeking an outstanding PhD candidate to develop
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Classification Title: RES AST SCTST Classification Minimum Requirements: PhD in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Machine Learning or a closely related
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and specific competences: Essential qualifications A master’s degree (120 ECTS or equivalent), completed by enrolment, in computer science, electrical or computer engineering, robotics, machine learning
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at Saxion University of Applied Sciences, you will contribute to the development of machine-learning models that connect powder characteristics and process parameters with the properties of the final
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23 Sep 2026 Job Information Organisation/Company KU LEUVEN Department faculty of engineering science Research Field Computer science » Computer systems Computer science » Database management
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and memory systems. This effort is truly trans-disciplinary, drawing on biodesign/biotechnology, machine learning, and interaction design. This project builds on groundwork already underway in our group
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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, Robotics, Electrical Engineering, or a closely related field. A strong academic record and solid background in machine learning and deep learning. Ability to develop, understand, and critically evaluate
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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems
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mission of the Norwegian Maritime AI Center is therefore to accelerate operationalization of AI in the maritime value chains. The objective of the research is to use machine learning methods to find models