Research Fellow

Salary:

As this vacancy has limited funding the maximum salary that can be offered is Grade 7, salary £36,024 

Contract Type:

Fixed Term contract up to March 2025

The Department of Civil Engineering at the University of Birmingham is seeking to appoint a research fellow to work on the recently funded UKRI research grant VPP-WARD (https://www.vppward.com/).

The successful candidate will be responsible to lead the research works that looks into developing numerical models to simulate the impact of climate anomalies and extreme scenarios on buried power grids and their supporting ground. This will be done through developing multi-phase modelling of ground and buried utilities using finite element analysis as well as developing physics-informed machine learning predictive models. Through this we intend to capture impact of climate change events such as floods and draught, and their consequence such as large deformation ground movements, on buried utilities and distributed energy resources. The predictive models will be used to estimate model grid resilience and simulate future extreme environmental scenarios. The project also aims to use data from potential experimental set ups in the National Buried Infrastructure Facility (NBIF), where available.

Summary of the role:

• Work within the VPP-WARD research grants and supporting the project team
• Lead research works on developing numerical models
• Analyse and interpret research findings and results
• Writing reports, scientific journal papers and presenting at international conferences based on the project findings
• Contribute to licensing or spin out deals with demonstrated commercial success (such as revenues, asset or company sales, IP generated) and/or public understanding of the discipline or similar
• contribute to writing future bids

Person Specification

• First degree in area civil engineering, a higher degree (or one near to completion) relevant to ground engineering or equivalent qualifications
• Experience of finite element modelling is essential
• Knowledge of large deformation FE analysis is desirable
• Knowledge of machine learning numerical methods is desirable
• Ability of data analysis and data presentation are essential
• High level analytical capability
• Ability to communicate complex information clearly
• Fluency in relevant models, techniques or methods and ability to contribute to developing new ones
• Ability to assess resource requirements and use resources effectively
• Understanding of and ability to contribute to broader management/administration processes
• Contribute to the planning and organising of the research programme and/or specific research project
• Co-ordinate own work with others to avoid conflict or duplication of effort
• Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly

Informal enquires to Asaad Faramarzi, email: a.faramarzi@bham.ac.uk

To download the full job description and details of this position and submit an electronic application online please click on the 'Apply' button above or visit our careers website.

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