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developed the SPARCED pipeline to convert structured lists of species, parameters, and reaction types into an SBML (Systems Biology Markup Language) model file, and we created a model based on one
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principled new models and methods, for modern machine learning problems. Machine learning recently has been largely advanced by differential equation-based frameworks, such as generative diffusion models
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and collaboration across AI/ML, sensing, modeling, and control. A publication pathway spanning AI for science/instrumentation, process systems engineering, and control. Mentor programme as a new
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+ years of experience with agent-based models or physics-based models 5+ years of experience managing a scientific team of 5 or more people 2+ years of experience working with a product management team to
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are looking for a postdoctoral researcher to be based at the University of Minnesota to advance hydrologic modeling of low-relief, peatland-dominated watersheds. Specifically, we are looking to implement a new
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-based models that optimise and control pharmaceutical manufacturing processes effectively. Your main responsibility is to develop and enhance discrete element models (DEM), integrating physics-based
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Design Lab – works on modelling, control and optimization for mechatronic systems, industrial robots and processes (https://dynamics.ugent.be ). We are part of the department of Electromechanical, Systems
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part of the jointly promoted NEUROLYMPICS – Neuro-Centric Multimodal Control System project, focusing on preliminary studies, technical specifications, modelling and system design. The work to be
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-the-loop (HIL) validation. The Research Staff will contribute to the design, modelling, simulation, validation, and optimization of electric vessel power systems, with strong emphasis on battery-based
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preprocessing impact model performance. Results will support more efficient experimental design and smarter manufacturing control. Career Readiness Competencies: Communication Critical Thinking Technology