Research Associate (831090)

FTE: 1.0
Term: Fixed for 24 months

The Department of Chemical and Process Engineering (CPE) within the Faculty of Engineering is seeking to recruit a Research Associate to develop novel carbon measuring metrics to achieve Carbon Circular Economy. Machine leaning based work will be carried out on thermodynamics, kinetics and catalysis of decarbonisation technologies including biomass valorisation, CO2 conversion, waste plastic recycling, etc. This position is one of the three PDRA positions being recruited for one UKRI funded project with an overall aim at reshaping a fossil-free feedstock carbon supply to accelerate net-zero.

The position requires prior experience in Machine Learning, and background on Thermodynamics/kinetic Analysis and Catalysis are preferred. The postholder will be responsible on Machine Learning work of the key reactions, evaluating the role of operating conditions and catalyst performance, and developing a new carbon measuring metrics built upon traditional Life-cycle Assessment techniques. The postholder will work closely with the principal investigator, other Research Associates, and the PhD students, that involved in this project.

As a Research Associate, under the general guidance of a research leader, you will develop research objectives, play a lead role in relation to a specific project/s or part of a broader project, conduct individual and/or collaborative research, contribute to the development of new research methods, and contribute to the securing of funds for research. You will write up research work for publication, individually or in collaboration with colleagues, and disseminate the results via peer reviewed journal publications and presentation at conferences. You will join external networks to share information and ideas, inform the development of research objectives. You will collaborate with colleagues to ensure that research advances and you will collaborate with colleagues on the development of knowledge exchange activities by, for example, participating in initiatives which establish research links with industry and influence public policy and the professions. You will co-supervise student projects, provide advice to students and contribute to teaching as required by, for example, running tutorials. You will contribute in a developing capacity to Department/School, Faculty and/or University administrative and management functions and committees and engage in continuous professional development.

To be considered for the role, you will be educated to a minimum of PhD level in an appropriate discipline, e.g., Chemistry, Chemical Engineering, etc, or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in Machine Learning, Thermodynamics, and Catalysis, and a developing ability to conduct individual 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.

Whilst not essential for the role, applications are welcomed from candidates with relevant work experience.

Applicants may use tools such as AI to support their application; however, all submissions must accurately reflect their own experience and understanding. The University reserves the right to verify the authenticity of application materials and may reject applications where concerns arise.

Informal enquiries about the post can be directed to Dr Xiaolei Zhang, Reader (xiaolei.zhang@strath.ac.uk).

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