Early Stage Researcher position (ESR5) as part of the project XP-RESILIENCE, call H2020-MSCA-ITN-...

Employer
University of Sannio, Benevento, Italy
Location
Italy
Posted
August 31 2017
Position Type
Full Time
Organization Type
Academia

The University of Sannio, Benevento, Italy (https://www.ding.unisannio.it/) welcomes applications from Early-Stage Researchers (ESRs) with an excellent track record to the XP-RESILIENCE project (Horizon 2020 - Marie Sklodowska-Curie Action - ITN - 2016). This is a prestigious scheme with the objective of supporting the career development and training of researchers - with a focus on innovation skills, and offers a 3 years contract with attractive working conditions and high quality professional opportunities. The candidate, if selected, will be enrolled in the Doctoral Study Programme "Information Technologies for Engineering"  (http://www.unisannio.it/it/amministrazione/avviso/a20170257) and start working on October 2017.


About XP-RESILIENCE


XP-RESILIENCE is an inter/multi-disciplinary project including seven academic partners, one Institute of applied science and seven private companies from ten different European countries. XP-RESILIENCE intends to establish a network of individual research projects working towards Advanced Modelling and Protection of Complex Engineering Systems against NaTech Disasters which will contribute to the strengthening of community resilience.


Research Group


NaTech risk analysis of industrial facilities is a new area of expertise for the Structural and Geotechnical Group of the Department of Engineering at the University of Sannio. The group is led by Professor Luigi Di Sarno (http://www.unisannio.it/it/user/643/curriculum).


Individual Research project


The selected candidate will be working on the following topic:


Title: Soil-structure interaction analysis of critical infrastructures of petrochemical plants


Objectives: Implementation of stick models of critical components of infrastructures for time-efficient analysis to perform versatile yet accurate risk-based, including soil-structure interaction. These models will serve as a means to perform QRA.



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