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Field
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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18 Sep 2026 Job Information Organisation/Company KU LEUVEN Research Field Computer science » Informatics Engineering » Biomedical engineering Engineering » Computer engineering Biological sciences
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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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positions for general criteria for the position. Preferred selection criteria Education or experience combining engineering or transport with data-driven and quantitative methods Experience with railway
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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance
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, computer science or AI, games technology, animation/VFX or a related discipline. We are looking for an independent, enthusiastic and driven candidate with experience in at least one of the following areas
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Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms
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in one or more of the following: railway engineering, infrastructure maintenance, rolling stock, condition monitoring, sensor data analysis, statistical modelling, machine learning, life-cycle cost
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engineering, and model building for financial datasets. At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run