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that you contribute to the development of the Renovation Digital Twin concept (led by Saxion). Essential activities within your project will be to: · model data standards for design of renovations
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of the Open Competition Domain Science-M programme (Twenty-one innovative research projects awarded through Open Competition Domain Science-M programme | NWO - https://www.nwo.nl/en/news/twenty-one-innovative
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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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will use computational models to explore the minimal functional requirements for self-replication to emerge from polymerising molecules. Instead of simulating specific chemistries in full detail, we will
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
, you will use computational models to explore the minimal functional requirements for self-replication to emerge from polymerising molecules. Instead of simulating specific chemistries in full detail, we
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reconstruct the structural models, with an emphasis on picking and combining the right techniques, as well as quantifying the uniqueness of information obtained. Position Overview: You will develop an in-house
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PhD Position on Modelling the Evolution of the Larsen C Ice Shelf Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 15 May 2025 Apply
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, engineering, informatics, or a related field. Proven experience in energy system modeling, preferably with PyPSA or a similar framework. A strong understanding of energy system modeling and optimization
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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, applying advanced modeling techniques and analyzing large-scale datasets to contribute to healthcare policy decisions. The PhD project will be supervised by Dr. Nora Franzen and Professor Maarten J. IJzerman