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methodologies in machine learning and causal inference applied to human health. Read more about NCRR here . Your job responsibility With a motivated, interdisciplinary team of approximately 70 researchers and
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the interplay between qualitative and quantitative methods and data. There is a growing focus on novel computational methods such as NLP, machine learning, and AI within the group. Teaching activities in
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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. These include, but not limited to: Research Question 1: How can multimodal UAV data (RGB, thermal, LiDAR, hyperspectral) be fused using machine learning to predict complex canopy traits such as water-use
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threats, and safe NLP models, contributing to a safe and secure society. Using insights from Cybersecurity to improve systematic security in NLP models. The candidate should have an MSc. in Machine Learning
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journals and conferences in your field. Secure funding for your research area from both Denmark and the European Union. Teach, guide, and supervise BSc and MSc students, as well as supervise PhD students
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, including bias mitigation and reinforcement learning techniques. Proficiency in Python and standard NLP libraries (e.g., Hugging Face and PyTorch). CHC is a research and development unit at Aarhus University
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make buildings smarter and more sustainable? Join us to advance your career by working
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, MATLAB, and/or C++/C#) Knowledge of machine learning techniques, particularly for time-series data Background in prosthetics or human-machine interfaces is advantageous PhD Stipend 2: Adaptive Control