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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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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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Hunger Lab at Tilburg University, and four industry partners. In this project, you will develop and advance optimization models and algorithms to support decision-making in food supply chains, with
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participate in the training and dissemination events of the MSCA Doctoral Network ANT . You will develop signal processing algorithms and protocols for AirComp, and implement and validate them in simulation
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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Networks, and ICT Services & Applications. Your role Design intelligent agent architectures leveraging large language models (LLMs), planning algorithms, and secure transaction protocols tailored
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 26 days ago
related to staff position within a Research Infrastructure? No Offer Description The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic