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actively contribute to the NCER-D2ET (Data-Driven Energy Transition Digital Twin) project, a national strategic initiative to develop Luxembourg’s energy digital twin platform. NCER-D2ET aims to design and
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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the key features of real leaves, and conduct similar experiments in the wind tunnel and in a commercial leaf gas exchange apparatus (LI-6800), with the goal of testing hypotheses about the effect of leaf
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; · Experience in using NMR, GPC, FTIR, DMA, dilatometry, DSC, TGA, or mechanical testing will be considered as an asset; · Notions in life cycle assessment (LCA) and the safe and sustainable by design
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experience designing and deploying automation and control architectures that span from edge devices (e.g. grid-forming converters, IoT controllers) to cloud-based platforms. Practical knowledge of distributed
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Engineering or a related technical field. Strong proficiency in model-driven or model-based system design, includes domain specific languages, data and system modelling, model transformations. Experience in
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: Extensive experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and
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Applications should include: Curriculum Vitae - detailing your education and research experience, your publications, any awards, and any other activities or interests that you deem relevant Cover
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experiments with quantitative microscopical analysis and physics-based modelling to understand how conifers solve the challenge of solute transport against the flow of water through the needle, and what
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(semiconductor and microelectronics sector, instrument manufacturers) · Defining, elaborating and testing novel scientific and technological concepts and designs for charged particle beam technologies