Department: Chemical and Process Engineering

Faculty: Faculty of Engineering

Contract Type: Fixed Term (12 months)

Working Arrangements: Hybrid. The standard requirement across the University is that at least three days per week (based on 1FTE) will be spent working on-site (with flexibility as appropriate).

On Site Facilities: Car parking, sports centre, catering.

Holidays: 31 days + 11 statutory days. Option to purchase additional holidays.

Pensions: Contributory pension scheme available to all staff including generous employer contribution.

Training: Professional Development with Organisational and Staff Development Unit (OSDU) plus external training if required.

Family Friendly Benefits: Generous parental leave provision, on-campus nursery and options for flexible working.

Health and Wellbeing: University Sport centre, Occupational Health service, access to health and wellbeing events, cycle to work scheme, Employee Assistance Programme, agile working and established carers support network and carer friendly policies.

The department of Chemical and Process Engineering are seeking a highly motivated and skilled Research Associate to work on an innovative industry-funded project, led by Dr Leo Lue and Dr Jun Li, focusing on the development of a transformative technology for Oil & Gas well decommissioning. You will be a core part of an interdisciplinary research team working closely with our Industrial Partner to validate, predict, and optimise the performance characteristics of the technology in the conditions found in Oil and Gas wells. You will carry out multi-physics modelling of multiphase reacting flows and heat transfer in high-pressure water systems using a variety of finite element modelling tools, including ANSYS and NGSolve.

To be considered for the role, you will be educated to a minimum of PhD level in Chemical Engineering or Thermal Engineering, or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in multiphysics modelling, particularly using ANSYS, programming in Python, and a developing ability to conduct independent research work, to disseminate results and to prepare research proposals. You will have an ability to plan and organise your own workload effectively and an ability to work within a team environment. You will have excellent interpersonal and communication skills, with the ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences.

Applicants are required to complete an application form including the name of three referees who will be contacted without further permission, unless you indicate that you would prefer otherwise. Please click the s1jobs APPLY button now.

Informal enquiries about the post can be directed to Dr Jun Li, Reader (jun.li@ strath.ac.uk).

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