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machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position Requirements: The successful candidate is expected to: Build and evaluate chemical
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. The ideal candidate should have a strong background in artificial intelligence and machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position
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) Positions Postdoc Positions Application Deadline 7 Oct 2026 - 23:59 (Europe/Copenhagen) Country Denmark Type of Contract Temporary Job Status Full-time Hours Per Week 37 Offer Starting Date 1 Dec 2026 Is the
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-time appointment (37 hours per week) for 38 months, from 1 November 2026 or as soon as possible thereafter. The position is based in Aalborg, Denmark. Project Description We are seeking a highly
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Conducting evaluation and impact assessment of the Innovation Academy, including register-based analyses of innovation and entrepreneurship activities Developing and delivering courses and learning activities
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; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics
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at least one of the following: a PhD degree related to circular design innovation in the circular economy, preferably in the area of apparel/textiles; or equivalent experience in a different sector; or a