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of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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in IEEE Communications Society’s and IEEE Signal Processing Society’s journals and conferences. Strong background in communication theory, signal processing, machine learning, and optimization theory
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Torbein Kvil Gamst 26th April 2026 Languages English English English Faculty of Science and Technology Postdoctoral Research Fellow in Machine Learning Apply for this job See advertisement
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renewed each semester Requirements Minimum of enrolled/completed Master?s degree in a science field or current enrollment in a PhD program. Instructional experience of at least 2 years preferred. Past
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-edge tools and machine learning techniques to model spatial multi-omics data. The aim is to advance our understanding of protein dynamics at the single-cell level and contribute to a broader
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flexibility. Responsibilities include conducting behavioral neuroscience experiments—including vapor self-administration and operant conditioning tasks (such as attentional set-shifting and reversal learning
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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, energy consumption, and packet loss. The use of distributed machine learning provides a relevant solution to mitigate the lack of communication reliability [3][4]. This PhD proposes to guide the learning
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and deep understanding of machine learning, artificial intelligence, algorithms, and knowledge of the latest developments in AI. Proficiency in ML tracking/monitoring tools (MLflow, Grafana) and LLM
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optimization or machine learning methods relevant to materials research. 4/2/2026