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.0c02887 ). We are looking for a motivated student with keen interest towards experimental research and applications of trace gas analysis. An optimal candidate should have prior experience with optical
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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 previously introduced in
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technologies to facilitate efficient optimization of the enzymes and products. The applications of this research span enzyme technologies to functional biomaterials. Scientific environment The Department
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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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.0c02887 ). We are looking for a motivated student with keen interest towards experimental research and applications of trace gas analysis. An optimal candidate should have prior experience with optical
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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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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