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are at the core of anomaly detection and despite being a well-established field of research, these are still very much open problems. To this end, we are looking for candidates interested in developing new machine
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or related fields (with the degree obtained no longer than four years before the application deadline. Exceptions can be made with documented career breaks eg parental leave, illness, mandatory military/civil
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dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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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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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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biodiverse crops and agricultural practices to mitigate the effects of climate change on global food production: https://novonordiskfonden.dk/en/news/climate-resilient-crops-novo-nordisk-foundation-and-the
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reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop
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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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technologies Development and utilization of high throughput methods for characterizing and quantifying the physicochemical behavior of food macromolecules in complex matrices. Modelling and the use of machine