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. We envisage combining process-based modelling and machine learning, as well as integration of Earth observation data into the modelling framework. The objective is to quantify the GHG budgets
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with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction or a related field who enjoy making empirical, methodological, and technical contributions
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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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at the interface between mechanics and machine learning? We are looking for a postdoctoral researcher for a fixed term, full time position at the Department of Materials and Production on Aalborg campus, starting 1
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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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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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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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against different operation conditions. The position is a part of a research project and prototype battery modules will be produced by one of the partners. The tasks include testing of these prototype