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to hard problems in the field of computer vision. The PhD student will develop a review of the state of the art, an in-depth investigation of the current use of quantum computers applied to machine learning
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) - Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. - English: demonstrated ability to write and edit scientific texts in English. Specific Requirements - Quantify
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). Optimize the databases linked to the data spaces, ensuring system scalability and reliability in a cloud environment. Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements
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FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 116329 Completion of a doctoral thesis on manufacturing process optimization through the implementation of Artificial Intelligence
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) for sustainable protein production and functional ingredient development. Design and implement experiments to optimize fermentation processes for the generation of protein-rich chickpea ingredients. Screen
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candidate will be expected to lead the preparation of national and EU funding proposals, collaborate closely with cross-functional teams, and lead or contribute to high-impact scientific publications. Where
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management operations meant to make network troubleshooting more rapid and effective. Selected students will work under the supervision of Vincenzo Mancuso. Students will collaborate with researchers and
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project will be linked to the ALGAEDIVERS project which investigates Mediterranean microalgae as sustainable sources for food and functional feed. It will focus on isolating new strains, optimizing biomass
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(or equivalent) degree in Telecommunication Engineering or Computer Science. Good knowledge of signal processing and artificial intelligence. Good knowledge of linear algebra and optimization tools
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degeneration in AD and the role of Tau at these early stages. We are looking for a motivated and highly collaborative person to join our emergent team. Main tasks and responsibilities: Her/his PhD research work