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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under
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Interatomic Potentials) code for ternary compounds with variable composition with crystal structure optimization algorithms (evolutionary, random, etc.); - Application of the CSP DFT/MLIP methodology to various
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funded by a EU programme Reference Number AE2025-0603 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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navigation. The task also includes the development of the necessary analytical and numerical methods and software tools. Candidates interested are encouraged to visit the ESA website: http://www.esa.int Field
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FARM-ID - Associação da Faculdade de Farmácia para a Investigação e Desenvolvimento | Portugal | about 1 month ago
Intelligence; Chemistry; Medicinal Chemistry. Candidate Profile: Master’s degree in Mathematics, Physics, Data Science, Chemistry, or related fields¹; Experience in implementing deep learning algorithms
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. The current position deals with free-space optical transmission experiments. It will involve challeges with low SNR, atmospheric turbulence issues, coherent recevers and related signal processing algorithms
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knowledge of collaborative software tools, and experience with the implementation of data acquisition or analysis algorithms You have a good track record of published articles in peer reviewed journals
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develop and analyze mathematical models and algorithms that connect partial (and/or stochastic) differential equations, infinite-dimensional optimization, and statistical machine learning. The goal is to