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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Engineering Laboratory, we develop model-based methods for designing and controlling ultra-precise systems. Building on the Dutch design principles legacy of van den Hoek, Koster, and Soemers, we specialize in
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-driven methods to optimise large-scale renovation flows (Verbouwstromen). By bringing together contractors’ resources, clusters of buildings, and smart operations planning, PRE-MADONA accelerates
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Organisation Job description In the Engineering and Technology Institute Groningen (ENTEG), we are looking for a talented and motivated PhD candidate on electrochemical ammonia synthesis in Protonic
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will focus on developing novel AI-driven methods for modelling, estimation and control of brain dynamics – time-dependent patterns of neural activity fundamental to brain function, behaviour and
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candidate will have strong data-driven methodological learning opportunities with high social impact on cancer care organisation. They will work within an interdisciplinary team, applying advanced modeling
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Research and Logistics group at Wageningen University, the Zero Hunger Lab at Tilburg University, and four industry partners. In this project, you will develop and advance optimization models and algorithms
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, and are motivated to understand and re-engineer complex biological systems. Additionally, you bring: a MSc degree in (bio)physics, (bio)chemistry, or a related field; experience working in a wet lab and
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population projections and management of wild bird populations in times of climate change”, with the Seychelles warbler (Acrocephalus sechellensis) as a model system. The project is supervised by Prof. Hannah