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-guided machine learning. You are quick to assimilate information and capable of independent research. Experience in the pharmaceutical sector is an advantage You speak and write English fluently. You are
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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are comfortable working with Git and API tooling, such as Postman. You have experience in machine learning, NLP/LLMs, multimodal systems, computer vision, or scraping. Having experience in data science
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wireless communications, RF signal processing, and/or applied machine learning Strong background in digital communications and RF signal processing, ideally with experience in SATCOM, NTNs, or space-borne
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systems, with a focus on 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
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, Electrical Engineering, Aerospace Engineering or a related field, with a focus on Robotic Perception and learning based methods Demonstrated expertise in at least one of the following areas: Machine Learning
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including the study of online control, motor adaptation, eye-hand coordination, decision-making, human-machine interaction, and other state-of-the-art paradigms used in current research in systems
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/knowledge of computer science and/or machine learning Interest/knowledge of omics data analysis, gene regulation or structural modeling Proficiency in programming languages such as Python, R and/or C++ as
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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the catalyst’s dynamic evolution. The goal is to select model systems based on the complex reaction networks involved in the CO2-to-hydrocarbons process, using machine-learned models for a consistent