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interaction); (iii) querying the knowledge base about what was useful in the past to predict actions that might be useful in the present, try them out and update its knowledge base (i.e. update learning). Also
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international conferences Excellent programming skills, with demonstrated ability to develop research-oriented software Experience with digital twin environments for testing and validation Excellent communication
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research-oriented software Experience with digital twin environments for testing and validation Excellent communication skills in both oral and written English * The date shown in your doctoral degree
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. Familiarity with software development workflows, tools, and practices (e.g., IDEs, CI/CD, testing, documentation). Experience in empirical software engineering, AI prototyping, or human-AI interaction studies
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model accuracy against experimental benchmarks Collaborate on the development of testing methodologies for protective device evaluation Machine Learning Integration Develop and implement machine learning
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involve established software tools, such as: CHEMKIN-PRO for steady one-dimensional simulations of laminar flames with detailed chemistry. CONVERGE for unsteady three-dimensional simulations of turbulent