Prospective Life Cycle Assessment for Sustainable Chemical Innovation: Developing Digital Techniques for Early-Stage Decision Support

Details

Are you passionate about shaping a sustainable future and making a real difference in the chemical industry? An exciting doctoral opportunity awaits you at the intersection of cutting-edge technology and environmental sustainability assessment.

Accurately predicting the potential environmental impacts of low technology readiness level (TRL) chemical production routes once they are fully deployed is a significant challenge for the chemical industry. The goal of this PhD is to explore how prospective / ex-ante LCA, covering multiple impacts, can be applied in the context of early-stage innovation of sustainable chemicals. This is required to inform innovation decisions contributing to net zero and other environmental sustainability ambitions.

This EngD will focus on developing and applying innovative digital tools and techniques to achieve this goal, despite the limited primary data availability and the lack of maturity of sustainable chemical production routes. The LCA tools developed will include aspects of machine learning and data mining to enable gap-filling algorithms and probabilistic modelling of future scenarios. The focus will be on providing a time-efficient, reliable sustainability assessment of chemical ingredient production for fast-moving consumer goods, with a special emphasis on complex chemicals that could be sourced from biomass and/or captured CO₂.

During the doctoral project, you will work closely with a dynamic team of LCA experts at Unilever’s Safety and Environmental Assurance Centre and the University of Sheffield. Together, you will develop a robust assessment framework that can guide vital business decision-making. Your work could have a considerable impact, contributing directly to the mission of achieving net zero and fulfilling ambitious environmental sustainability goals.

Our ideal candidate possesses:

• A good honours degree (2:1 or above) (or equivalent) in a relevant field, for example, but not limited to, Chemical Engineering, Computer/Data Science, Environmental Engineering, etc.
• A keen interest in systems thinking and modelling.
• Proficiency in or willingness to learn programming languages like MATLAB, Python, VBA, etc., to solve complex engineering challenges.
• Passion for sustainability and some familiarity with environmental impact modelling approaches such as Life Cycle Assessment (LCA)
• Self-motivation, exceptional time management, resilience, and perseverance.
• Keen attention to detail and ability to apply this within a meaningful context.
• An enduring curiosity and a love of learning.

Supervisors

• Prof Rachael Rothman, Dr Fanran Meng, University of Sheffield
• Dr Florence Bohnes, Dr Katy Armstrong, Unilever

Please apply to the University of Sheffield. 

Informal enquiries may be sent to ​Prof. Rachael Rothman ([email protected]) and Dr Fanran Meng ([email protected]). Please note that applications sent directly to this email address will not be accepted.