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- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); Published today
- Delft University of Technology (TU Delft); today published
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symptom networks; and Preferred skills in programming, quantitative analysis, and handling complex datasets. Strict MSCA eligibility requirements: You must not hold a doctoral degree at the date
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on developing a new multi-disorder prediction approach that integrates different sources of information. You work with analytical model development, extensive simulation studies and analysis of existing large
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. Academic training in cutting-edge computational analysis and design tools. Structured training through network-wide workshops, summer schools, and transferable-skills courses. International secondments
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the design and analysis of such models. PhD position 1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD
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policymaking? Would you like to contribute to research that turns large-scale network analysis into actionable policy insights? Do you want to work in an interdisciplinary environment of leading researchers and
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several critical requirements: first, the geometry and size of the vascular network should be representative of real (tumor) microvasculature, i.e. consisting of 3-dimensional networks of perfusable lumens
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highly interdisciplinary research environment combining experimental neuroscience, biophysical modeling, and clinical data analysis, embedded in a strong national and international network. Your salary and
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biotypes; within-target personalized coil positioning, using MRI-guided neuronavigation and network-based metrics to optimize stimulation for each individual; n-of-1 trial design in clinical care, embedding
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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developing state-of-the-art methods in network analysis, connectomics, and computational neuroscience. You will collaborate within a motivated, multidisciplinary team of PhD students and postdocs with