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Postdoc position: A Resilience Engineering Tool to Measure the Stability of Complex Systems in the P

ETH Zürich

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Postdoc position: A Resilience Engineering Tool to Measure the Stability of Complex Systems in the Process Industry


Research in the Laboratory of Reliability and Risk Engineering (www.rre.ethz.ch) of the department of Mechanical & Process Engineering (D-MAVT) at ETH Zurich is aimed at the development of innovative techniques and hybrid analytical and computational tools suitable for analyzing and simulating failure behavior of engineered complex systems. We are looking for a

Postdoc position: A Resilience Engineering Tool to Measure the Stability of Complex Systems in the Process Industry

A postdoc is sought to conduct the research project "A Resilience Engineering Tool to Measure the Stability of Complex Systems in the Process Industry" supported by Swiss Re Risk Engineering and the Reliability and Risk Engineering Laboratory at D-MAVT. The primary objective of this project is to develop a tool to detect and predict dangerous operating conditions of industrial plants with application to the petroleum and petrochemical industry, and to assess the resilience of the current operations by identifying and quantifying relevant system key performance indicators (KPI).

The tool will use information relevant KPIs and expert judgment to assess the current level of stability and ability to recover, i.e. the resilience of the system. The subjective expert judgment is integrated in the assessment through quantification and propagation of subjective probabilities. The tool must have the capability to trace and predict the dynamic change of system resilience. The dynamics of the industrial plant is expected to be represented though a reduced-order model, using (possibly limited) information from the system side, and provide a prediction of the risks to operations.

The project is expected to progress broadly through five phases:

1) Review and update of the "substantial" risk quality variables Risk quality variables are any technical properties, technical/non-technical key performance indicators, organizational, cultural, economic or other factors that are believed to affect the ability of the system 'process plant' to cope with disturbance and/or prevent major accidents.

2) Network modelling (connectivity) The interdependency (or connectivity) matrix among the individual risk quality variables is developed. The goal is to identify the mutual influences, the feedback loops and the causal dependencies that relate individual risk quality variables.

3) Identification of dynamical properties In this phase, the rules of inter-dependency and non-linearity between the system elements, which were identified in Phase 2, are defined. The connectivity among the individual risk quality variables is complemented with dynamical properties.

4) Development of system resilience indicators In this phase, the system properties/variables are identified. The resilience indicator is synthesized from the dynamic response of the system properties/variables to perturbations.

5) Development of a resilience tool to assess risk in the process industry Implementation of the newly developed methodology into a risk assessment tool.

The developed model will be used by insurance companies to achieve a clearer picture of the risk profile of their current petroleum/petrochemical clients, and by the industry itself to increase awareness of its own risk profile, understand the ability of the system to absorb disruptions and to recover from disturbance.

The research will be undertaken in the group of Prof. Giovanni Sansavini (D-MAVT) and benefit from the interaction with Swiss Re Risk Engineering.

The successful applicant will have a strong working knowledge of the key methodologies used for dynamic simulations (network modelling, system dynamic, discrete event, agent-based modeling), which will allow him/her to choose from, or combine the methods as required. A good understanding of the concept of resilience, strong numerical / conceptualization skills, system thinking, an open and curious mindset, and a highly motivated, proactive personality with good communication skills round off the candidate's profile.

Working in a top-level research environment, the candidate will have a unique opportunity to develop further their research abilities. The position is available until filled.

Please submit your application online (Apply now) which includes a motivation letter (addressed to ETH Zurich, Mr. Ueli Lott, Human Resources, CH-8092 Zürich) , a comprehensive CV, academic records and references and upload all documents (pdf is recommended).


Apply now