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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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to recruit a talented researcher for a 2-year, full-time postdoc in machine learning from 1 October or soon thereafter. Your work tasks We are looking to recruit an excellent postdoctoral fellow to apply
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the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power electronic conversion, energy and hydrogen storage, downstream processes
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electronic conversion, energy and hydrogen storage, downstream processes, and energy demand—to enable more efficient, flexible, and economically viable Power-to-X operation. This position is expected to start
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At AAU Energy, a position as Postdoc in thermal processes in power to X technologies is open for appointment from 1st October 2026 or as soon as possible hereafter. The position is available for a
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: Overcoming Inequity in Embodied Learning in Danish Vocational Education and Beyond, funded by Independent Research Fund Denmark. This is a full-time (37 hours per week), fixed-term (24 months) postdoctoral
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others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
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within this field. Your work tasks In this position you will conduct research within Computer Vision and Deep Learning, with a particular focus on the development of an AI-powered framework
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IMADA uniquely brings mathematicians and computer scientists together within a single department to foster theoretically well-backed, high-quality data science research. The department is home to numerous