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ERC Advanced Grant “De Tenebris” (PI: G. Bertone) and develop precision models of binary black holes in astrophysical and dark matter environments. Join Us! You will join the GRAPPA centre of excellence
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of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about
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elements with controllable stiffness. The project will involve analytical and computational modelling, as well as designing and conducting lab experiments. Key questions include: How to create materials
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embedded within the Soft Tissue Engineering and Mechanobiology (STEM) group headed by Prof. Carlijn V.C. Bouten and the Modelling in Mechanobiology (MMB) group led by Dr. Sandra Loerakker . As a member of
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models based on survey and secondary data. Creative approaches to combining and leveraging various data sources are highly encouraged! The selected Ph.D. candidate will benefit from our outstanding
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appendages using the (halo)archaea as a model. Studying the infection mechanisms of archaeal viruses can provide insight into the evolutionary history of viruses and help to understand adaptation to extreme
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. As part of this PhD, the candidate will: - Conduct an integrative review of established competency models - Create assessment tools (which may include use of AI tools) to measure CLMA proficiency
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explore how to combine data-driven and model-based approaches to assess the quality of returned parts, monitor in-process performance in real time, and support intelligent decisions on remanufacturing
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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environments. The project will build on an interdisciplinary approach, combining concepts and methods from physics, chemistry, and mathematical modelling. The long-term goal is to derive design principles