10 computer-programmer-"https:"-"https:"-"https:"-"https:"-"FEMTO-ST" positions at Amsterdam UMC
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and apply them in clinical studies across different disease areas to generate novel biological insights. As part of the network-wide training programme, you will collaborate with leading international
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and apply them in clinical studies across different disease areas to generate novel biological insights. As part of the network-wide training programme, you will collaborate with leading international
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. Supporting compound screening and evaluating the efficacy of potential pharmacological therapies. Working with researchers across the POLARIS consortium and contributing to the network-wide training programme
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with researchers at CING and across the POLARIS consortium. You will also participate in the POLARIS network-wide training programme and planned secondments. This gives you the opportunity to develop
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. Throughout the PhD project, you will have opportunities to further develop your scientific and transferable skills through the POLARIS doctoral training programme.
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of the POLARIS training programme, you will undertake planned secondments that complement your research at the University of York. At Zantiks , you will gain hands-on experience with behavioural
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will work in Dr Fleur Tjong’s group (TjongLab) embedded in the Amsterdam Center for Computational Cardiology under co-supervision prof. dr. Folkert Asselbergs at Amsterdam UMC, location AMC. Our
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organoids. Depending on your background and interests, the project can focus more on establishing and characterising these models or on the computational integration of multi-omics data. Both aspects will be
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Vrije Universiteit Brussel (VUB) is the recruiting organisation for this position. You will be employed by the Molecular Imaging and Therapy (MITH) research group and embedded in the POLARIS consortium. Your academic supervision will be provided by Prof. Timo De Groof and Prof. Nick...
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procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries. The goal is to create patient-specific