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of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be conducted by Associate Professor Georgios Tsaousoglou and Head of Section Razgar
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by
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on the theoretical foundation of machine learning. Your CV comprises: A strong relevant background within machine learning and mathematics. Extensive experience programming machine learning models. An active interest
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approaches for the computational analysis of time-resolved data on reactions, contribute to teaching and supervising BSc and MSc student projects Qualifications You must have a two-year master's degree (120
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decision-making. Collaborate with international partners and contribute to joint research activities. Teach and co-supervise students at different levels in courses and associated projects. Publish and
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order to understand the context better. During the project you will complete a PhD education as described in the rules and regulations for the PhD programme. Project duration This is a three-year PhD
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than RGB will be actively researched. Exploring 3D canopy modelling and plant growth dynamics for digital twin integration. Self-supervised learning will generate multi-modal agricultural pre-trained AI
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interaction between experimental and theoretical activities. You will join a thriving community of researchers and benefit from a strong network of international collaborators. Our work environment is
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will be part of the section of Artificial Intelligence, Cybersecurity, and Programming Languages (ACP), an ambitious group that fosters collaboration, research excellence, and quality education. The