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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
The Department of Digital Design and Information Studies within the School of Communication and Culture at Aarhus University invites applications for a postdoctoral position “Human AI Collaboration
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grant project “Driving innovation in crop resilience through Comparative QTLomics.” The selected candidate will contribute to five main objectives: 1. Apply large language models (LLMs) to collect
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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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differentiation. The position will focus on designing and executing experiments involving Cas9 based perturbation, single cell multi omics method development, and downstream verification in transgenic cell lines
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packages aim to transform consumers from passive observers into active participants in circular economy practices in food services – through evidence on barriers and motivators, co-designed digital
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to learning Danish, including reading, writing, and speaking, is expected during the employment period. Contact Further information on the position may be obtained from Professor Margit Bak Jensen
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strategies and market positioning. Job description The successful candidate is expected to contribute to the overall objectives of the project by being involved in design, implementation, data collection, and
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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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