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Qualification Type: PhD Location: Naples - Italy Funding for: EU Students, International Students Scholarship amount: €19,000 per year (before social contributions) for up to 4 years, provided in monthly instalments (increased by a maximum of 50% for previously authorized research stays abroad;...
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for global health 2. Civil Engineering and Architecture 3. Electronic and Computer Engineering 4. Industrial Engineering 5. Neuroscience 6. Innovation Science and Technology Notice of competition and specific
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the computerized procedure "PICA - Integrated Platform for University Competitions”, at the address https://pica.cineca.it/login .from the date of the publication of the present Notice of Competition to 23rd
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experience. This PhD project investigates how such radio signal cues can be identified, selected, and integrated into learning-based navigation frameworks. Research Objectives: The PhD candidate will
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of the general MSCA-DN project RENOVATE (Regenerative engineering innovation in early intervention of osteoarthritis). This project aims the following main objectives: Define patient-specific key functional and
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and other effectors (such as antimicrobial peptides) against specific pure culture bacteria by using methods developed in objective i); iv) analyse in silico and metaproteomics phageome present in
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imaging of energy storage materials, with the focus on detection of light elements and monitoring of electrochemical processes. The research will be conducted primarily at the accelerator facility
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-economical society requirements. Objectives The research aims to study and verify the durability of a widespread historical construction technique, i.e. earthen mortars (also used for plasters), and their
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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. The main objective of the scientific activities of DC 11 will be the implementation of selected climate-related equations to LCA modelling frameworks. After an opportune selection of the equations, they will