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for improving knowledge in design, optimization and decision support for novel and sustainable construction materials. The candidate should also possess demonstrated experience in the area of AI/ML and concrete
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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skills and experience in written, spoken, and collaborative work in English. What we offer: A career path optimized for transition to industry. You will be affiliated with the dynamic Aalto Scientific
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of LIDAR systems, especially FMCW LIDAR architectures Programming experience in MATLAB or Python for data analysis Hands-on experience building and optimizing test setups for photonic devices We are looking
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irreversible changes, and not only in environmental systems and land use, but also in terms of market or institutional structures, need to be anticipated and accounted for in optimal policy design. The research
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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model
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, the appointee’s work will cover some of the following areas: Development of an isotope version of the process-based CH4 model and parameter optimization for different wetland types. Coupling the updated CH4 model
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fully automated Prompt calibration which can save tens of person years, millions of CPU hours and speed up the typical CMS analysis cycle times by several years. In addition, it allows better optimization