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these exiting domains. Topics include but are not limited to remote direct memory access, hardware offloading and acceleration, AI for networking and security, storage management, cryptography, and architecture
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security concepts. Experience with embedded platforms, FPGA development, or hardware-accelerated computing will be considered an advantage. Familiarity with technologies for deploying AI on constrained
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the Carlsberg Semper Ardens Accelerate grant for this project. Co-supervisors will be Associate Professors Lina Fogt Jacobsen and Helle Alsted Søndergaard . Job description The PhD projects will contribute
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-driven biocatalysis and accelerate bioprocess development. DC1: Machine learning-guided multiparametric optimisation of cytochrome P450 monooxygenase PhD enrolment: Technical University of Denmark DC2
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;dtu.dk You can read more about BRIGHT at https://novonordiskfonden.dk/en/projects/bright/ and you can read more about the hiring department at https://www.biosustain.dtu.dk/ If you are applying from
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Villalobos) and Consortium partners (https://cordis.europa.eu/project/id/101227645 ). Our focus is to guide innovation at an early stage by assessing the benefits (society, economic and environmental
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systems, digital twins, and resilient structural design. We are looking for a motivated, curious, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials
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, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery
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robotic research platform and an automated ‘Device Doctor’ for perovskite solar cells. The goal is to combine high-throughput experimentation, machine learning, and advanced modeling to accelerate device