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developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with the running infrastructures. Using
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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funded research project “Navigating volatility in different welfare state contexts (VOLARE)”. This project analyses how social policy design interacts with the month-to-month income variability experienced
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close interaction with academic and industrial stakeholders. The ideal candidate: holds a Master's degree in Engineering Technology, Bioscience Engineering, or a related discipline. has a strong interest
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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We are seeking a motivated and creative PhD student to develop the next generation of AI-driven protein design methods that explicitly account for protein–lipid and protein–membrane interactions
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interact to coordinate replication and encapsidation remains unclear. This means that improvements in rAAV manufacturing approaches are mainly empirically driven and incremental at best. In this project
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well as the modelling of plasma chemistry, plasma reactor design, and plasma-catalyst interactions. Your research will focus on non-thermal plasma playing a pivotal role in the electrification of the chemical industry
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focusing on three societal grand challenges and their interaction: digitalization, diversity and democracy. Where to apply Website https://www.uhasselt.be/en/about-hasselt-university/working-at-hasselt
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exceptional optical activity, for strong and predictable enantioselective interactions with nanoscale biological entities, such as proteins and amyloid fibrils. Three-dimensional (3D) investigation of the NPs