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Field
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algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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cryptography guarantees better performance and faster speed for encrypting data. Without doubt, AES (Advanced Encryption Standard) and Keccak/SHA-3 (Secure Hash Algorithm 3) are the two most used and famous
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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, integrity-aware multi-domain navigation benchmark and associated algorithms, tested in realistic operational environments. The outputs will support standardisation efforts, accelerate cross-domain navigation
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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
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wing panels. Reliable process control is critical: underheating leads to poor bonding, while overheating causes polymer degradation. At the heart of process control algorithms lies a physics-based
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and