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Design invites applications for a PhD stipend in the field of secure machine learning within the general study programme Electronic and Electrical Engineering; as per November 1, 2026, or as soon as
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in AI, bioinformatics, statistics, computer science, data science, machine learning, epidemiology, or related fields with a relevant PhD degree (required). Experience with analyzing large genetic data
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of secure machine learning within the general study programme
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professors, two postdocs, and five PhD-students. The group focus on high-quality applied research. The current topics of interest in the group include student learning, transitions and career, teacher
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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Perception Lab. Your competencies You have a strong background in computer vision and artificial intelligence, documented by a relevant PhD degree in, for example, computer science, machine learning, computer
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computational methods as the necessary foundation to venturing and expanding the field through modern approaches in machine learning and artificial intelligence. The appointment is hosted by the Department