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, or as soon as possible thereafter Project Description We invite applications for a postdoctoral position at the interface of computational proteomics, machine learning, and mass spectrometry. The
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Machine Learning Employer University of Southern Denmark (SDU) Location Odense, Fyn (DK) Salary Competitive Closing date 16 Nov 2026 View more categories View less categories Discipline Chemistry
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programming in Python, R, or similar languages Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to
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machine learning for plant biology Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 12 Oct 2026 View more categories View less categories Discipline
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a two-year postdoctoral position focused on physics-driven machine learning for ground-based, airborne, and
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materials science, and machine-learning-driven materials discovery. The successful candidate is expected to have experience in areas such as high-throughput DFT calculations, thermodynamic and phase
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employment. Publication Track Record: At least two first-author research papers at flagship venues of core machine learning research (e.g., NeurIPS, ICML, ICLR, AISTATS). Theoretical Rigor: A deep
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teaching assistantship duties. Expected Skills and Qualifications: We are seeking a candidate with a strong desire to make significant contributions to fundamental machine learning research
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intersection of polymer processing, materials science and Machine Learning to develop dynamic recipes for sustainable plastics. In a typical plastics production line, several types of materials are fed into
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, machine-learning methods and predictive calculations of defects and transport properties. The position will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing