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application and machine learning. • Author of at least 2 research papers in topics related to the project. • Knowledge on advanced control systems and optimization (please attach a description of your
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hydrogen-ammonia co-combustion using experimental techniques, high-fidelity numerical simulations, and machine learning” The competition is open to applicants who meet the detailed requirements set out in
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• experience in working with a synthesizer (knowledge of phosphoramidite chemistry preferred) • ability to prepare the text of a scientific publication and present the results • knowledge of computer programs
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, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
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skills. Experience in protein work (construct preparation, prokaryotic expression systems, protein purification using AKTA or NGC systems). Knowledge of bioconjugation techniques for attaching small