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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in developing computational Social Network Analysis (SNA) methods
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Sklodowska-Curie Doctoral Network FADOS. The successful candidate will join a cohort of 17 doctoral students based at 16 research groups in Europe and the UK. About FADOS FADOS, Fundamentals and Applications
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European Marie Sklodowska-Curie Doctoral Network FADOS. The successful candidate will join a cohort of 17 doctoral students based at 16 research groups in Europe and the UK. About FADOS FADOS, Fundamentals
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candidate/MSCA fellow for the project: “MHT in the 21st century.” The position is part of the EU-funded Marie Skłodowska-Curie Actions Doctoral Network MenoBrain “Brain Health in Menopausal Women” with full
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are inviting qualified applicants to apply for a doctoral student position in the European Marie Sklodowska-Curie Training Network programme FADOS. The successful candidate will join a cohort of 17 Doctoral
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are inviting qualified applicants to apply for a doctoral student position in the European Marie Sklodowska-Curie Training Network programme FADOS. The successful candidate will join a cohort of 17 Doctoral
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management in hip and knee arthroplasty Join the prestigious Marie Skłodowska-Curie Actions Doctoral Network SHIELD (Strategies for Healing Implant-associated infections and Enhancing Longevity in Devices) and
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biofilm-related infections in orthopaedic implants: from in vitro to in vivo models Join the prestigious Marie Skłodowska-Curie Actions Doctoral Network SHIELD (Strategies for Healing Implant-associated
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peptides as an infection control strategy in bone conduction hearing implants Join the prestigious Marie Skłodowska-Curie Actions Doctoral Network SHIELD (Strategies for Healing Implant-associated infections
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to conduct one's own postgraduate education. This includes, in addition to completing mandatory doctoral courses, using sequence analysis (including phylogenetics [both maximum-likelihood and Bayesian analysis