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. Any appointment is conditional upon submission of documentation confirming completion of the PhD degree. solid programming skills applied to machine learning algorithms, interactive systems, audio and
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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machine learning techniques to develop emulators for the theoretical predictions of various observables as function of cosmological parameters. The candidate will develop and use skills in topics such as
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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this by concentrating on five select research areas in ICT. Learn more about: working at Simula and careers at Simula Project/Job description In the Department of ComplexSE, we are now offering a
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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of the post. Candidates without a master’s degree have until 1st of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools