Research Fellow in Computational Chemistry and AI/ML for Sustainable Polymers – School of Chemistry – 106956 – Grade 7 Full-time

Research Fellow In Computational Chemistry And Ai/Machine Learning

School of Chemistry, College of Engineering and Physical Sciences

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £36,636 to £46,049 with potential progression once in post to £48,822

Grade: 7

Full Time, Fixed Term contract up to October 2030

Closing date: 30th March 2026

Travel may be required for this role

To create and contribute to the creation of knowledge on the EPSRC-funded Prosperity Partnership research project entitled 'Mission biodegradability: Foundations for the sustainable future of formulated polymers.

We are seeking a Research Fellow in Computational Chemistry and AI/Machine Learning to advance the state of the art in understanding the degradation and biodegradation of water-soluble polymers used, or with potential for use, in formulated products. The primary focus of this role will be the development and application of computational chemistry, molecular modelling, and data-driven (AI/ML) approaches to analyse polymer physicochemical properties and degradation behaviour across different environments, with the aim of identifying key molecular-level design principles that enable environmentally relevant biodegradation.

The project is inherently multidisciplinary, forming part of the Mission Biodegradability Prosperity Partnership, and involves close interaction with postdoctoral researchers and PhD students investigating complementary experimental, environmental, regulatory, and microbiological aspects of polymer degradation across the Schools of Chemistry, Chemical Engineering, Earth and Environmental Sciences, Law, and Microbes, Infection and Microbiomes, as well as collaboration with multiple industrial partners.This post will be hosted in the group of Professor David O. Scanlon in the School of Chemistry. The Research Fellow will contribute computational insight that integrates with these wider activities to support the development of predictive frameworks for sustainable polymer design. You will have appropriate research experience to undertake this project, alongside a proven ability to conduct and publish research in polymer science/computational chemistry.

The Research Fellow is expected to contribute to a wide range of research activities, under the direction of the Principal Investigator (PI), Professor David O. Scanlon, responding to academic needs and timelines as required.

To undertake computational chemistry research, polymer modelling, and machine-learning-based prediction of polymer biodegradations under the supervision of Prof. David Scanlon.

To produce regular written and oral reports pertaining to the project as requested; attend regular project meetings; give regular presentations to the group; write papers for publication in peer reviewed scientific journals.

To work as part of a team and play an active role in the project management of the prosperity partnership within the Scanlon Materials Theory Group, participating in all group meetings and activities. You may help to supervise research students, be responsible for installation and maintenance of equipment and training of personnel on equipment.

Participate in the collaborative meetings and work with the project collaborators.

The responsibilities may include some but not all of the responsibilities outlined below.

Perform research and collect data in the specified area to a high level of competency and quality.

Provide guidance and supervision to support staff and students in the group.

Maintain a high level of knowledge of the immediate and surrounding literature.

Undertake management/administration arising from research including organising project review meetings.

Contribute to developing new ideas, directions, techniques and methods in order to advance the project and enhance its quality.

Analyse and interpret data generated from all aspects of the project.

Apply knowledge in a way which develops new intellectual understanding.

Contribute to writing scientific papers and bids for research funding.

Disseminate research findings by oral and other presentation in a range of fora from group meetings to research seminars and conferences etc.

Contribute to Departmental/School research-related activities and research-related administration.

Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader.

Deal with problems that may affect the achievement of research objectives and deadlines.

Promote equality and values diversity acting as a role model and fostering an inclusive working culture.

A first degree in area of specialism.

Has obtained or is preparing to defend a higher degree (PhD) relevant to research area or equivalent qualifications.

Excellent research profile in the area of in the area of computational chemistry, polymer modelling, and machine-learning/AI.

Demonstrated experience with machine learning methods applied to scientific problems, preferably with materials or polymer datasets.

Proficiency in Python and scientific computing libraries; familiarity with machine-learning frameworks and data processing tools.

Experience with molecular modelling or simulation tools (e.g., LAMMPS, GROMACS, or similar) and ability to design and analyse simulation workflows.

Strong analytical skills with the ability to interpret and synthesise complex computational and experimental datasets.

Interest in interdisciplinary research and willingness to learn new techniques.

Ability to keep up to date with new developments in the fields relevant to the project.

Ability to work both independently and as part of a team on research programmes.

Adept at analysing and interpreting data.

Able to apply knowledge in a way which develops new intellectual understanding.

Excellent interpersonal and communication skills including the ability to work effectively in a multi-disciplinary project area of research.

Ability to plan, organise, implement and deliver programmes of research work to tight deadlines.

Ability to guide and manage research of others.

Ability to write and give presentations to both national and international audience standard and communicate complex information clearly.

Ability to install and maintain relevant equipment and to train other personnel on operation of this equipment.

Co-ordinate own work with others to avoid conflict or duplication of effort.

Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly.