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, cognitive science, art history, and creativity studies exploring digital interfaces that facilitate collaboration between humans and AI algorithms. We are located at the Department of Management at Aarhus BSS
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employment This is a 7-month position from October 1st, 2025, or as soon as possible. Job description You will participate in the ongoing development of an algorithm platform for digital shadows and twins
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standard fine-tuning. Key research objectives include: Developing efficient algorithms: exploring and designing training strategies (e.g., supervised finetuning, reinforcement learning, or new alignment
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of prior data?) Additional research topics may include: Algorithmic Transparency and Fairness in Funding Decisions Comparative Analysis of Funding Models AI-Driven Predictive Analytics for Funding Success
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, data-driven methods based on omics. Techniques applied will comprise advanced 4D cellular and molecular imaging (e.g. lattice lightsheet SIM, genetically encoded sensors for subcellular and synaptic
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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence