Research Associate (630483)

We seek an ambitious, creative RA to undertake an exciting, challenging research project collaborating with a strategic industry partner. The successful candidate will be responsible for supporting modelling and analysis to provide an evidence-base to support key engineering decisions related to technology selection for sustainable marine vessels.

FTE : 1
Term: Fixed Term (12 months)

Our Department

The Department of Management Science has a vibrant intellectual culture, and our academic staff have a strong record of both publication and generating funding through research and knowledge exchange activities. Our educational portfolio includes an undergraduate principal subject in the Strathclyde Business School as well as our MSc in Data Analytics, MSc Business Analysis and Consulting, and an MSc in Health Analytics, Policy, and Management. Details about the department can be found at http://www.strath.ac.uk/mansci/.

The Opportunity

The project will develop and evaluate a novel decision-support model that can be used by the industry partner to evaluate technology choices for sustainable marine vessels, and to produce useful information that enables effective communication to a range of stakeholders. The successful candidate will be responsible for supporting modelling and analysis to provide an evidence-base to support key engineering decisions. As a Research Associate you will be involved in developing rigorous models to support assessment of the impact of technology innovations across a range of relevant performance indicators given uncertainties associated with future use environments. You will contribute across key modelling activities, including computational probabilistic modelling, elicitation of subjective probabilities, empirical data collection, developing and delivering written and oral reports and journal articles, and engaging with the industry and other key partners.

You will work with the Management Science research team of Professor Lesley Walls, Professor of Practice Matthew Revie, and Dr Euan Barlow. Under their guidance, you will play a lead role in the project, conduct individual and collaborative research, contribute to the development of new modelling methods, and contribute to planning for future proposals. You will write up research for publication and disseminate the results via peer reviewed journal publications and presentation at conferences. You will join external networks to share information and ideas, collaborate with colleagues to ensure that research advances inform our educational provision, and you will collaborate with colleagues on participating in initiatives which strengthen research and scholarship with industry.

To be considered for the role, you will be educated to a minimum of PhD level in an appropriate discipline (e.g., Operational Research, Statistical Science, Mathematics, Industrial Engineering, Management Science), or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in probability modelling, elicitation, and inferential analysis. You will be able to conduct individual research work and to disseminate results. 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.

Formal interviews for this post will be held on August/September 2024

Informal enquiries about the post can be directed to  Dr Euan Barlow, Senior Knowledge Exchange Fellow (euan.barlow@strath.ac.uk), Professor Lesley Walls (lesley.walls@strath.ac.uk), Professor Matthew Revie (matthew.j.revie@strath.ac.uk).

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