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) interest in high-performance computing and algorithm optimization (e.g. GPU computing) ability to work both independently and in collaboration within a multidisciplinary research environment initiative and
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geometry. Additionally, we leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those
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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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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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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