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Overview
The Leverhulme Centre for Climate Change Mitigation (LC3M) is one of four winners of the Leverhulme Research Centre awards, designed to support fundamental cross-disciplinary research across the whole range of the sciences, humanities and social sciences. Professor David Beerling FRS is the Director of LC3M which has been awarded £10m over a period of ten years, to address one of the greatest challenges facing humanity in the 21st Century: global climate change. The vision for LC3M is to develop and assess the role of enhanced rock weathering (ERW) as a means of safely removing large amounts of CO2 from the atmosphere to cool the planet while also mitigating ocean acidification. Professor Lenny Koh leads the social sciences stream on supply chain economics in the LC3M, where we are seeking to appoint an outstanding Post Doctoral Research Associate on geo-spatial prospective Life Cycle Assessment (LCA) and transport network analysis to join the team. They will be reporting to Professor Lenny Koh working collaboratively with the LC3M and the cross disciplinary team
The University's Advanced Resource Efficiency Centre (AREC) and Management School will be the host of this appointment, working in close partnership with the LC3M. This is a full-time position for 12 months with a proposed start date of 01/01/25.
Main duties and responsibilities
- Geo-spatial analysis using Geographical Information Systems (GIS) capability.
- Prospective Life cycle assessment (LCA) through coding, e.g. Python.
- Transport network analysis and operational research methodologies.
- Advanced data science, Artificial Intelligence (AI) and Machine Learning (ML) capability.
- Modelling of Enhanced Rock Weathering (ERW) supply chain, transport network and environmental sustainability impact.
- Scenario modelling of ERW and its supply chains using geo-spatial analysis, LCA, transport network analysis and AI/ML.
- Integration of traditional/Process LCA with Environmental Input-Output LCA.
- Multi-scale modelling at countries and decades scales.
- Integration of modelling, experimental and field trials data for sustainability prediction, monitoring, reporting and verification (MRV) and business model scale up.
- Theorising ERW, negative emission technologies, climate change, supply chain, resource flow, net zero, carbon neutrality and carbon credit accounting.
- Multi-methods advances across disciplines.
- Defining requirement of machine learning and cloud infrastructure to enable large scale data storage, processing and advanced analytics, dynamic modelling; and implement them.
- Undertaking high-quality research in line with project demands.
- Writing academic papers in line with the Centres' demands.
- Undertaking extensive literature research on science, social science and engineering based journals.
- Bids writing and proposals writing in line with the Centres' demands.
- Presenting in conferences and meetings about the research work.
- Communicating with cross disciplinary research teams, policy makers, NGO, scientists, social scientists and stakeholders in this research.
- Understanding, analysing and interpreting advanced ERW research in Themes 1-3, and integrating with the work in Theme 4.
- Supervising PhD students and early career researchers in this field.
- Carry out other duties, commensurate with the grade and remit of the post
Person Specification
Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.
Essential criteria
- PhD in Environmental Science, Sustainable Supply chain, Life Cycle Assessment (LCA), Management Science/Operations Research, Environmental Economics, Geographical Information Systems (GIS), Computer Science/Artificial Intelligence (AI)/Machine Learning (ML)) or relevant subject (or equivalent experience) (assessed at: application)
- Excellent record of high-quality publications for appropriate career stage (assessed at: application)
- Experience in geo-spatial analysis and geographical information systems (GIS) (assessed at: application, interview)
- Experience in supply chain and transport network analysis (assessed at: application, interview)
- Experience in quantitative data collection and analysis, especially in Life Cycle Assessment (LCA) and/or developing mathematical indicators and large-scale datasets and database analytics including advanced statistical analysis of atmospheric CO2 data, climate change data, OECD data, Ecoinvent data etc. (assessed at: application, interview)
- Prospective LCA capability through coding, e.g. using Python. Experience in LCA and Input-Output (I/O) analysis, and experience of LCA Tool and I/O databases. (assessed at: application, interview)
- Experience in computational and quantitative advanced scenarios, AI and ML modelling including computer programming and coding. (assessed at: application, interview)
- Effective communication skills, both written and verbal, report writing skills, experience of delivering presentations. (assessed at: interview, presentation)
- Experience of working in a multi-disciplinary team and independently. (assessed at: application)
- Experience of project management and the ability to manage resources and workload effectively. Excellent due date delivery. (assessed at: interview)
- Excellent organisational skills and the ability to undertake some administrative duties. (assessed at: interview)
Desirable criteria
- Experience in bids and proposals writing and development. (assessed at: application)
Further Information
Grade: 7 - £37,999
Duration: 12 months
Line manager: Professor in Operations Management
Direct reports: N/A
For informal enquiries about this job contact
Professor Lenny Koh, Professor in Operations Management: on s.c.l.koh@sheffield.ac.uk
Next steps in the recruitment process
It is anticipated that the selection process will take place on 6th February 2025. This will consist of a short presentation and an interview. We plan to let candidates know if they have progressed to the selection stage on the week commencing 20th January and full details will be provided to invited candidates. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process you can contact mgt.hr@sheffield.ac.uk.
Our vision and strategic plan
We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window).
What we offer
- A minimum of 41 days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more.
- Flexible working opportunities, including hybrid working for some roles.
- Generous pension scheme.
- A wide range of discounts and rewards on shopping, eating out and travel.
- A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women's and Parent's networks).
- Recognition Awards to reward staff who go above and beyond in their role.
- A commitment to your development access to learning and mentoring schemes; integrated with our Academic Career Pathways
- A range of generous family-friendly policies
- paid time off for parenting and caring emergencies
- support for those going through the menopause
- paid time off and support for fertility treatment
- and more
More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).
We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.
We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision ( www.sheffield.ac.uk/vision ) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.