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to both technical metrics and educational outcomes. Responsible AI and fairness auditing. Conduct algorithmic fairness validation of the CLARA system, develop documentation on data governance and GDPR
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, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms, memory technologies, and neuromorphic hardware architectures for future
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work to segmentation algorithms with computer scientists. It is a preference if you additionally have experience in performing interdisciplinary research together with another scientific specialty
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data, code, models, and documentation in a way that supports findability, accessibility, interoperability, and reusability. A willingness to learn new algorithms, tools, and developments in AI, including
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given to those with expertise in two or more of the following areas relating to the position: AOCS subsystem architecture, design, testing and verification, including control algorithm design and tuning
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fundamentals (TCP/IP, client-server model, sockets, and API communication tools like Postman/curl); solid grasp of data structures & algorithms, plus exposure to vector databases and Retrieval-Augmented