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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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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD position – Ad Print4Life DC11 Reference code: 50156132_2
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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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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 10 hours ago
Degree PhD Course location Kaiserslautern Teaching language English Languages Discussions are held in English (100%). Programme duration 8 semesters Beginning Only for doctoral programmes: any time
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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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positions) : the deadline depends on the respective advertised open positions. Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No
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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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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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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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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