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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
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modelling, advanced machine learning tools, etc. We welcome applicants with a strong academic background within engineering or applied science, whose expertise supports the development of resilient and
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piglets who are unable to acquire own mothers’ colostrum. The majority of the experimental in vivo work is located at Frederiksberg Campus, albeit but with some investigations under commercial farming
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Sustainability in association with Professor Christina Lioma and her Machine Learning research team in the Department of Computer Science at the University of Copenhagen. The sub-package focuses
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. To achieve this, the Center will develop and deliver research-based education for the future workforce – spanning bachelor, master, PhD, and life-long learning. The Center is based upon grant funding of DKK
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are part of a sub-project on Algorithmic Sustainability in association with Professor Christina Lioma and her Machine Learning research team in the Department of Computer Science at the University