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Field
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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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safety and computational social choice and develops formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research
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. The Role Faculty of Environment, Science and Economy The successful applicant will contribute to the project NATALIE by developing AI algorithms that integrate data from various sources to better understand
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Overview We are seeking an experienced researcher to develop decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international research programme
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an interdisciplinary team that works on cutting-edge questions ranging from mathematics and theoretical physics all the way to numerical simulation algorithms? Then apply now to join our team of researchers in
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer interaction, as well as participate in the full range
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Systems via Proof Certificates, and focus on the design, development, and application of Safe RL algorithms as well as their verification via Proof Certificates, including monitoring and shielding of cyber
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to evaluate and advance machine learning algorithms for one of the following application areas: “Characterising forests variations in relation to distance from pre-Columbian earthworks in the Amazon forest
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aims to develop algorithms for discovering patterns that are robust to data changes. They are expected to co-develop the problem definitions, design reslience measures, co-developing and implementing