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Field
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analysis, with possible specialisations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. This is based on perspective and
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aims and objectives This project aims to develop an optimised, fault-tolerant implementation of the Falcon post-quantum digital signature algorithm for spaceborne FPGAs/processors. The key objectives
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Media (EDM), the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms, Implementations (RTG π³), the UBRA AI Center for Health Care , and the ZeMKI
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scientists from, e.g., Sociology, Political Science, or Economics. The PhD candidate will also develop state-of-the-art optimisation algorithms specifically tailored to the proposed large-scale network models
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, programming, algorithms, and data analysis skills Outstanding research skills Applicants with Master degrees by research with technical publications and research experiences in structural dynamics and
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://cheddarhub.org The work is envisioned to have great impact on design and development of intelligent AI/ML orchestration algorithms in real 6G experimentation test beds. The applicant is envisioned to further
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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the form of a human-expert informed reward function. Second, we aim for the integration of low-energy machine learning algorithms, so that the resulting AI model can run on a variety of devices, including
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workspaces under positional restrictions. Develop smart control algorithms that will allow the robotics end-effectors to communicate with the central control system and coordinate tasks with other end