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gain valuable knowledge and skills in training machine learning models and applying Natural Language Processing (NLP) techniques such as Topic Modeling and Named Entity Recognition. Additionally, you
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-on computational laboratories covering data curation, molecular representations, machine learning models, deep learning, generative models, and applications in reactions, catalysis, and spectroscopy. Coordinate with
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-source scientific software library. You will be part of a larger project at the Uncertainty in Complex Systems lab (PI: Dr Max Hinne) aimed at learning which statistical and/or computational model is most
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statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical
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19 Sep 2026 Job Information Organisation/Company Radboud University Research Field Computer science » Modelling tools Computer science » Programming Engineering » Computer engineering Engineering
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completion / submission) in a related subject area or relevant industrial experience. · Have expertise in Large Language Models, Natural Language Processing, Machine Learning and Responsible AI. · Proven
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discoveries made in the laboratory with meaningful improvements in patient care. You will be part of a research environment that values curiosity, creativity, scientific rigor, and continuous learning while
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. • Analyse data and develop scenarios/simulations. • Develop and implement generative machine learning models to generate plausible scenarios. • Econometric modelling on manpower
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computer applications, online resources, and other technologies for the classroom. Demonstrated proficiency using an online learning management system such as Blackboard to develop and build course content
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learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a