At a Glance
- Tasks: Join a groundbreaking project converting agricultural waste into eco-friendly bio-coal.
- Company: Northumbria University, a top-ranked institution for student experience and teaching quality.
- Benefits: 35 days annual leave, access to research facilities, and opportunities for international fieldwork.
- Other info: Collaborate with international partners and contribute to high-profile research projects.
- Why this job: Make a real impact on sustainability while advancing your research career in a dynamic environment.
- Qualifications: MS/PhD in relevant fields and experience in thermochemical conversion or machine learning.
The predicted salary is between 32963 - 40289 £ per year.
About the Project
SAFER PLUS is a £1.25 million Innovate UK-funded project developing Pakistan's first full-scale plant for converting agricultural waste cotton stalks and sugarcane bagasse into engineered bio-coal pellets through torrefaction. The bio-coal directly replaces imported fossil coal in textile mill boilers and brick kilns at 40–50% lower cost, with substantially reduced emissions. The demonstration hub is being established at the University of Kamalia, South Punjab, in partnership with Eco Research Limited and Pakistani textile industry partners. Northumbria University is now recruiting two Research Associates to join the SAFER PLUS team. These are distinct but complementary roles, and candidates should clearly indicate in their application which post they are applying for.
Post 1: Research Associate in Thermochemical Conversion and Biomass Processing
The Role
You will lead the scientific characterisation and optimisation of the torrefaction process for Pakistani agricultural waste feedstocks. Working directly with the Principal Investigator, you will design and conduct experiments, produce validated fuel quality data, and generate the technical evidence base that underpins SAFER PLUS's commercial and regulatory case.
Key Responsibilities
- Conduct thermogravimetric analysis (TGA) at multiple heating rates to characterise cotton stalk and sugarcane bagasse pyrolysis and torrefaction kinetics
- Develop and validate kinetic and thermodynamic models for the torrefaction process under industrially relevant conditions
- Characterise feedstocks and bio-coal products using XRD, FTIR, BET surface area analysis, SEM-EDS and proximate/ultimate analysis
- Determine gross calorific value (GCV), moisture, ash, volatile matter and sulphur content of bio-coal products under varying process conditions
- Investigate the effect of feedstock blend, moisture content, torrefaction temperature and residence time on bio-coal quality and consistency
- Contribute to peer-reviewed publications and project reports
- Support knowledge transfer activities with the University of Kamalia and industrial partners in Pakistan
Essential Requirements
- MS/PhD in Chemical Engineering, Materials Engineering, Energy Engineering or a closely related discipline (or equivalent research experience)
- Demonstrated experience in thermochemical conversion of biomass, specifically pyrolysis, torrefaction or gasification
- Proficiency in TGA, kinetic modelling and thermodynamic analysis
- Experience with materials characterisation techniques including FTIR, XRD, SEM-EDS or BET
- Strong publication record commensurate with career stage
- Ability to work independently and manage experimental programmes
- Excellent written and verbal communication in English
Desirable Requirements
- Experience with agricultural residue feedstocks particularly cotton stalk, sugarcane bagasse or wheat straw
- Familiarity with Pakistani or South Asian agricultural and industrial contexts
- Experience with proximate and ultimate fuel analysis for industrial applications
- Knowledge of cement, textile or brick kiln combustion requirements
Post 2: Research Associate in Machine Learning and Systems Integration for Clean Energy
The Role
You will develop and apply machine learning and data-driven modelling approaches to optimise the integrated SAFER PLUS energy system from feedstock characterisation through torrefaction to downstream combustion performance. You will work with experimental data generated by the project team and operational data from the demonstration plant to build predictive models that maximise bio-coal quality and system performance.
Key Responsibilities
- Develop ML predictive models (including but not limited to Random Forest, Gradient Boosting, Neural Networks) to predict bio-coal quality from feedstock properties and process parameters
- Build and validate process optimisation models integrating torrefaction conditions, feedstock blend and downstream combustion performance
- Design and implement a data acquisition and management framework for the SAFER PLUS demonstration plant at the University of Kamalia
- Develop real-time process monitoring tools and dashboards for plant operators in Pakistan
- Apply Python-based data science tools for model training, validation and deployment
- Collaborate with the thermochemical team (Post 1) to identify key process variables and translate model outputs into actionable operating guidance
- Contribute to peer-reviewed publications, particularly at the intersection of ML and biomass energy systems
- Support digital capacity building with Pakistani partner institutions
Essential Requirements
- MS/PhD in Chemical Engineering, Data Science, Energy Systems, Computer Science or a closely related discipline (or equivalent research experience)
- Demonstrated experience in machine learning applied to engineering or energy systems classification, regression and optimisation methods
- Proficiency in Python and relevant ML libraries (scikit-learn, TensorFlow, PyTorch or equivalent)
- Experience with process data analysis and handling industrial or experimental datasets
- Strong publication record commensurate with career stage
- Ability to translate complex model outputs into practical engineering guidance
- Excellent written and verbal communication in English
Desirable Requirements
- Experience with biomass, thermochemical or energy conversion processes
- Familiarity with IoT sensor integration and real-time data pipelines
- Experience with process simulation tools such as Aspen HYSYS, MATLAB or COMSOL
- Knowledge of South Asian industrial contexts or experience working with international research partners
Opportunities available to you
Both posts are fixed-term for 22 months, based at Northumbria University's Newcastle upon Tyne campus with opportunities for fieldwork visits to Pakistan. Northumbria University is ranked in the Top 10 in the UK for Student Experience and Top 15 for Teaching Quality (Times Good University Guide 2026). The SAFER PLUS team offers an internationally connected research environment with active programmes in Pakistan, Saudi Arabia and the UK. Both posts offer:
- 35 days annual leave plus bank holidays (pro rata)
- Access to Northumbria University research facilities and networks
- Opportunity to contribute to a high-profile internationally funded project with direct development impact
For informal enquiries about either post, please contact: Dr Jibran Khaliq, Associate Professor, School of Engineering, Physics & Mathematics; Dr Shahid Rasul, Associate Professor, School of Engineering, Physics & Mathematics.
Research Associate in Newcastle upon Tyne employer: University of Northumbria
Northumbria University is an exceptional employer, offering a dynamic work environment that prioritises safety and security while fostering a culture of inclusivity and collaboration. With a commitment to employee growth, we provide extensive benefits such as flexible working hours, generous holiday entitlement, and excellent pension schemes, all within the vibrant city of Newcastle upon Tyne. Join us in making a meaningful impact on the student experience and be part of a community that values academic excellence and innovation.
