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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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-3413 ), 4-Limited flight data for adaptive methods (doi.org/10.1016/j.geits.2022.100028 ), and 5- Failure to use a robust state estimator to increase robustness of EMS in eVTOL, have not been filled by
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 9 hours ago
-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures
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uncertainty characterisations for mass balance estimates from satellite altimetry applying the results in comparative studies and combination studies with complementary methods such as satellite gravimetry
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in developing new machine learning methods for multimodal data and
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: www.uni.lu/snt-en/research-groups/finatrax/ The candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with specialisation in Information Systems. In the context of Prof
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verifiability for AI systems, based at the Department of Computer and Information Science. These positions are funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Wallenberg AI
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tackling the above challenges with novel system designs and tailored AI/ML based methods. Candidate’s profile A First Class Bachelors degree and/or Masters degree in a relevant subject (computer
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer