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Are you passionate about uncovering and addressing vulnerabilities in AI systems, from algorithms to hardware? Join Us! We are looking for a highly motivated candidate with a computer security and
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been trained. The distributed nature of federated settings introduces unique challenges for unlearning: the central server never directly accesses raw data, information encoded in aggregated models can
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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the Nordic region and municipality/industry partners on real use cases for e-health solutions conducting research in software systems, distributed systems, network technologies and advanced data analysis
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candidate will design algorithms that identify suspicious model updates, reduce the influence of compromised UAVs, and preserve useful learning from honest UAVs operating with different data and unreliable
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning
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Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms
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, you will focus on developing mathematical models and numerical algorithms that systematically integrate uncertainties into the design process of optical systems. The goal is to enable novel design
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of compute processors. Today’s AI compute processors have multi-Terabit/s interfaces to share intermediate data for distributed training and processing, generating large traffic flows. Low and deterministic