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Applicants are invited for a PhD Fellowship/Scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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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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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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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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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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: Conceptualisation and synthesis of data integration and visualisation workflows. Data management and the development of knowledge graphs Development and application of AI and machine learning methods and pipelines
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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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