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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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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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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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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
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systems. The position offers an exciting opportunity to engage in cutting-edge research that addresses both theoretical challenges and practical applications. Key Responsibilities: Develop innovative
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heterogeneous multi-omics datasets. Integrative Data Analysis: Perform and lead analysis of large-scale multi-omics datasets, including RNA/DNA sequencing, methylation, and metabolomics. Method Development