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program with a project-adapted curriculum (training courses, lectures etc. on scientific, technical and complementary skill topics) and a strong PhD student community the opportunity for travel to present
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candidates (DCs) to pursue a PhD within the Network at different universities and industrial companies from 26 institutions across 11 countries (France, Germany, Ireland, Italy, Norway, Spain, Sweden
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personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich
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Your Job: In this PhD project, you will shape the future of power system security by harnessing exascale computing. Your research will focus on understanding and enhancing grid resilience under
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Hydrumedical, Braga, Portugal This PhD position is part of the EU-funded project Print4Life, a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof. Cecilia Persson, Uppsala University. Print4Life
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Description Clausthal University of Technology is a research-intensive university with a strong national and international network. The approximately 80 professors, 1,100 employees and 3,000
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breeding. More than 30 research groups study regulatory networks controlling fundamental traits such as reproductive development, organ geometry and growth, innate immunity and microbiome effects on plant
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications. Host: Helmholtz-Zentrum Hereon
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Models for Real-World Healthcare (MLCARE project DC3). The position is funded by the MSCA Doctoral Network MLCARE (Machine Learning Computational Advancements for personalized mEdicine). The MLCARE
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investigates how the gut microbiome shapes cognition and neuroinflammation during menopause, with a strong emphasis on computational modelling. We will reconstruct and simulate microbial metabolic networks