Research Fellow in Industrial Decarbonisation
- Employer
- Global Academy Jobs
- Location
- United Kingdom
- Salary
- £33,797 to £40,322
- Closing date
- Oct 8, 2020
View more
- Sector
- Science, Computer Science and IT, Computer Science, Chemistry, Chemical Engineering
- Hours
- Full Time
- Organization Type
- University and College
- Jobseeker Type
- Academic (e.g. 'Lecturer')
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Job Details
Would you like to contribute to the UK's foremost academic centre undertaking whole systems research for a sustainable energy future?
Do you want to further your career by applying your quantitative modelling skills to examine UK industrial decarbonisation strategies?
Do you enjoy working with researchers from other disciplines to tackle problems with significant potential for real-world impact?
The UK Energy Research Centre is undertaking research to explore how industry can dramatically reduce its greenhouse gases emissions by 2050, so helping the UK to meet its net-zero target. This will involve developing a model of manufacturing industry to analyse the deployment of existing and new technologies and infrastructure, as well as changes in the pattern of demand for materials and products. The research will take a whole-systems approach to industrial energy use that goes beyond the major energy intensive sectors. It will also explore how the availability of future infrastructure - such as hydrogen networks or carbon dioxide pipelines - could impact viable emissions reduction pathways for key industrial sectors.
You will be based in the School of Chemical and Process Engineering at the University of Leeds, which has an active research group on sustainable low carbon futures. The work is being led by Professor Peter Taylor and you will also work closely with other members of the UKERC industry team at the University of Bath.
You will have a PhD (or be close to completion) in a relevant engineering or other quantitative discipline with a track record of computer modelling or analysis, or equivalent experience that also demonstrates a significant track record of computer modelling or analysis, with a good level of numerical literacy and demonstrated ability to interpret complex data, and a demonstrated track record of quantitative analysis using MATLAB, Python, R or similar software.
To explore the post further or for any queries you may have, please contact:
Peter Taylor , Professor of Sustainable Energy Systems
Do you want to further your career by applying your quantitative modelling skills to examine UK industrial decarbonisation strategies?
Do you enjoy working with researchers from other disciplines to tackle problems with significant potential for real-world impact?
The UK Energy Research Centre is undertaking research to explore how industry can dramatically reduce its greenhouse gases emissions by 2050, so helping the UK to meet its net-zero target. This will involve developing a model of manufacturing industry to analyse the deployment of existing and new technologies and infrastructure, as well as changes in the pattern of demand for materials and products. The research will take a whole-systems approach to industrial energy use that goes beyond the major energy intensive sectors. It will also explore how the availability of future infrastructure - such as hydrogen networks or carbon dioxide pipelines - could impact viable emissions reduction pathways for key industrial sectors.
You will be based in the School of Chemical and Process Engineering at the University of Leeds, which has an active research group on sustainable low carbon futures. The work is being led by Professor Peter Taylor and you will also work closely with other members of the UKERC industry team at the University of Bath.
You will have a PhD (or be close to completion) in a relevant engineering or other quantitative discipline with a track record of computer modelling or analysis, or equivalent experience that also demonstrates a significant track record of computer modelling or analysis, with a good level of numerical literacy and demonstrated ability to interpret complex data, and a demonstrated track record of quantitative analysis using MATLAB, Python, R or similar software.
To explore the post further or for any queries you may have, please contact:
Peter Taylor , Professor of Sustainable Energy Systems
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