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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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centralization. Methods may include multiple regression, panel data models, difference-in-differences, and multilevel modeling. The postdoc will take part in the analysis to test hypotheses on how specific
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In this position, you will work on microscopy-integrable measurement technologies used to study three-dimensional cell culture models of breast cancer tissues. This PhD candidate position is
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automation, CAD design, programming, vacuum systems, machine learning and/or electronics is considered advantageous but not required Alignment with our core values What we offer Full-time, 4-year PhD funding
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Khakalo via email (sergei.khakalo@aalto.fi ) with the subject “PhD/Postdoc position in Computational Structural/Solid Mechanics”. In questions related to the recruitment process, please contact our HR unit