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research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in
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genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption of the methods. The project is carried out in close
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validation (V&V) techniques for space systems, software and algorithms with a focus on specific challenges of space-borne perception and proximity operations uncooperative spacecraft . Develop novel methods
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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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! ESRIC is conducting activities in three main areas: Research and testing facilities, Business support and incubation, and Community management. The primary objective of ESRIC is to research, develop and
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Transparency). The main tasks will be to: Develop AI-assisted tools leveraging large language models (LLMs) to support community-based fact-checking Designi and evaluate methods to improve the robustness
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to machine learning and AI projects for satellite systems. We are looking for a candidate capable of developing ML models and optimization algorithms specifically designed for highly dynamic satellite
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of particle-handling systems for the space environment, including the development of robust design criteria · Couple physics-based models and numerical simulations with optimization algorithms
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vulnerability assessment for satellite communications links Design, implement, and evaluate AI/ML‑based algorithms for real‑time detection, classification, and localization of jamming and spoofing signals using
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under