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Field
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. System Modeling: Develop and refine photonic system models incorporating key quantum mechanisms. Use simulation tools (Lumerical, Synopsys, Matlab, Python, …) to validate architectural feasibility and
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Perform molecular cloning, protein expression, and biochemical assays Conduct growth chamber experiments with model plant species Analyze genomic and transcriptomic data using computational tools Present
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven
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English in ISI indexed journals. b) candidates must have skills and previous experience in the following areas: i) experience in Finite Element Method modelling; ii) railway system modelling (vehicle and/or
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systems (e.g., GC) Experience in synthesis and characterization of heterogeneous catalysts Hands-on experience with (pressurized) chemical reactors Experience with modelling and simulation software (e.g
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-on experience with (pressurized) chemical reactors Experience with modelling and simulation software (e.g. Aspen) Good organization and data management skills We expect the candidates to be able to start
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter