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Destination Earth Climate Change Adaptation Digital Twin Project, Phase 3 (https://destine.ecmwf.int /), where INAR is a contributing member. The Climate DT project is setting up an operational simulation
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, Applied Mathematics, or a closely related field, with a strong background in AI/ML technologies, including algorithm development, optimization, and data-driven modeling. Candidates are expected
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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implement novel algorithms, formulating and solving human-centered AI problems. The Research Fellow will also support the development of partnerships with industry and government stakeholders, engage with
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experimental collaborators. The position is part of the Research Council of Finland project ELPH-ML (https://research.fi/en/results/funding/88752 ). In combination with academic development courses at Aalto
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out together with seven industrial partners and is externally funded by the Knowledge Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods
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of Finland project ELPH-ML (https://research.fi/en/results/funding/88752 ). In combination with academic development courses at Aalto University, we will help you grow a competitive and international career
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the profile of the Chair. The candidate will be offered support in scientific development, the possibility of participation in scientific projects, possibility of international cooperation. Where to apply E
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scientific development, the possibility of participation in scientific projects, possibility of international cooperation. Where to apply E-mail [email protected] Requirements Research FieldComputer
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languages like Python or C, and or developing and/or using computational methods for analyzing large datasets. Demonstrated experience in developing computational algorithms for solving problems, preferably