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processes, · You enjoy both modelling, model-data integration, data analysis and working with HPC. Scripting and programming experience are essential. · You like working in a team, explaining
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modeling, model-data integration, data analysis and handling large eddy covariance flux database. Scripting and programming experience are essential. ·You like working in a team, explaining and presenting
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. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ Candidates will be enrolled in the PhD program in Computer Science and Computer Engineering with
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE
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curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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Skills: Strong programming skills are an asset Soft Skills: Most importantly, we seek individuals who are curiosity-driven especially interested in interdisciplinary research, eager to continuously learn
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an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social