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Field
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digital twins for industrial chemical processes Process optimization and model-based decision support tools Development of computational tools for process monitoring and predictive analysis Candidate
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(3) Machine Learning (ML) approaches that improve determinism and predictability across IBF and APPF processes. This position supports an integrated program encompassing advanced control for IBF, APPJ
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skills by providing high-performance perception, decision and control functionalities based on AI model outputs that are controlled to be dependable and trustworthy. The selected candidate will join the
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functionalities that can further improve operational performance, such as the integration of predictive models, orbital dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
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between pollution control efficiency, electrochemical yield, and energy recovery potential; • Develop coupled electrochemical and hydrodynamic models to predict process behavior; • Participate in
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or robotic systems Knowledge of system integration, instrument control, workflow automation, and data acquisition Experience developing and applying AI/ML methods, including predictive modeling, active
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systems to operate safely and efficiently. Possible research directions include advanced flight control, model predictive control, nonlinear control, fault-tolerant control, cooperative control and aerial
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to the start of employment. Also, a current TB test will be required as a condition of employment. EEO/AA/M/F/Vets/Disabled. Minimum Qualifications Applicants should have an MS or PhD in computational biology