Research Fellow in AI and Computational Chemistry – Green Solvent Reactivity Modeling (UK)
Are you looking for a Research Fellow position in AI and Computational Chemistry focused on green chemistry and sustainable manufacturing? This opportunity combines machine learning, cheminformatics, and DFT-based modeling to accelerate the adoption of green solvents in industrial chemical synthesis.
This interdisciplinary research role is based at a leading UK research-intensive university and offers strong collaboration with industry partners and top academic institutions.
🌱 Why Green Solvent Research Matters
Traditional organic solvents are often toxic, volatile, and environmentally harmful. Although greener alternatives exist, solvent selection is typically addressed late in process development, resulting in:
Longer development timelines
Costly reaction re-optimisation
Increased uncertainty in scale-up
Early-stage AI-driven solvent prediction can dramatically improve reaction selectivity, efficiency, and sustainability.
🔬 Research Focus: AI, ML & Computational Chemistry
This project aims to develop solvent-dependent reactivity and selectivity prediction models by combining:
Machine learning algorithms
Cheminformatics descriptors
High-throughput DFT calculations
Curated reaction datasets from the literature
The goal is to predict reaction outcomes in green solvents using data from traditional solvent systems.
🧠 Key Responsibilities
As a Research Fellow, you will:
Build interpretable ML models for solvent-dependent reactivity
Analyse large-scale reaction datasets
Generate 2D and 3D molecular descriptors
Perform high-throughput DFT calculations
Design standard substrate sets for industrially relevant reactions
Use High Performance Computing (HPC)
Collaborate with experimental chemists and data scientists
Engage with industrial partners for real-world impact
🤝 Academic & Industrial Collaboration
You will work closely with:
University of Southampton – data mining and reaction curation
Imperial College London – experimental validation
Industry partners include:
Lhasa Ltd.
Molecule One
AstraZeneca
CatSci
Concept Life Sciences
These collaborations ensure the research is practically applicable and industry-ready.
🎓 Required Skills & Qualifications
PhD in Chemistry (or thesis submitted)
Strong background in computational chemistry
Proficiency in Python programming
Experience with machine learning models
Knowledge of DFT and molecular descriptors
Ability to work in interdisciplinary research teams
🌍 Impact on Chemical Manufacturing
This research will:
Enable early prediction of green solvent performance
Reduce waste and hazardous solvent use
Improve process sustainability
Accelerate industrial chemical development
Support net-zero and green chemistry goals
🏢 Work Location & Benefits
UK-based, hybrid working available
Eligible for Skilled Worker and Global Talent visas
42 days annual leave
Excellent pension & wellbeing benefits
Access to world-class research infrastructure
📩 Contact Details
Dr Bao Nguyen
Associate Professor
📞 +44 (0)113 343 0109
📧 B.Nguyen@leeds.ac.uk
https://jobs.leeds.ac.uk/Logon/?jobId=51041
❓ Frequently Asked Questions (FAQ)
What is AI in computational chemistry?
AI in computational chemistry uses machine learning models to predict chemical reactivity, selectivity, and properties based on molecular data and simulations.
Why are green solvents important?
Green solvents reduce environmental impact, improve safety, and support sustainable chemical manufacturing.
Is this position suitable for international applicants?
Yes, this role may be eligible for Skilled Worker and Global Talent visa sponsorship.
What programming skills are required?
Strong experience in Python, data analysis, and ML libraries is essential.
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