Research Associate in Numerical Modelling AI-Driven Sorbent- Carbon Capture Technologies

Overview

Role: Research Associate in Numerical Modelling for AI-driven Sorbent-Based Carbon Capture Technologies

Grade and Salary: Grade 7, £37,694 - £47,389 per annum

FTE and working pattern: 1

FTE, 35hrs per week, Monday – Friday

Contract: 12 Months FTC (Potential opportunity for extension)

Holiday Entitlement: 33 days annual leave plus 9 buildings closed days (and Christmas Eve when it falls on a weekday)

Purpose of Role: We are looking for a creative and highly motivated researcher willing to work as part of our international and multidisciplinary team with expertise to support our research activities in the engineering of optimal porous materials for CO2 capture applications via a data-driven and system-based approach (AI4

Capture). This position contributes to designing novel materials tailored for the most economical carbon capture process. The project involves the design of adsorption-based processes for screening materials and their integration into our techno-economic PrISMa platform, with the aim of identifying top performing materials for specific carbon capture applications.

The primary objectives of the research are: (1) to develop process models and cycle designs that can be integrated into our screening techno-economic platform; (2) to identify optimal targets for materials development for selected combinations of CO2 sources and sinks; and (3) to help develop data-driven approaches for speeding up the screening of materials and evaluating the performance of carbon capture processes.

The successful applicant must hold a PhD (or be about to obtain) in chemical engineering, mechanical engineering, physics or a related discipline (e.g., mathematics or other engineering) with background and demonstrable expertise in numerical modelling. The post is available from 1 March 2026 for 12 months in the first instance and could be extended further. See  for more details.

• Conduct collaborative interdisciplinary research on numerical modelling of sorbent-based capture plants and other modelling work to support the activities of the team
• Have strong experience in numerical modelling, preferably with Python
• Collaborate with the AI4
  
  Capture project partners to integrate process models with materials science, techno-economic analysis and life-cycle analysis
• Work collaboratively with the team to achieve project goals, including coordination of interdisciplinary teams, supervision of students/junior researchers and maintenance/support of facilities/equipment
• Prepare technical reports, posters and presentations for progress meetings, advisory board meetings and other dissemination activities
• Project coordination with other partners, work both independently and as part of a team to achieve milestones, liaising with team members, project partners and sponsors
• Progress a primary research project while contributing to other projects, e.g., supervising junior group members and PhD students
• Contribute scientifically through scholarly dissemination of research via reports, publications, presentations and travel to meetings
• Analyze and interpret results, generate original ideas, prepare proposals and applications to external bodies, and identify new research areas
• Assist the development of student research skills and contribute to assessment in teaching and supervision duties
• Develop research objectives and proposals, conduct individual and collaborative projects, and use relevant research techniques
• Contribute to planning of research projects and development of grant/contract proposals; build internal and external contacts for future collaboration
• Demonstrate good communication skills and maintain an appropriate publication record
• Continue to update personal knowledge and skills within the specialist research area
• Be involved in outreach activities with roles that can be tuned to preferences of the candidate, including interviews, talks for the general public and preparation of experimental demonstrators

• Education, Qualifications and Experience
• PhD (or about to obtain) in chemical engineering, mechanical engineering, physics or a related discipline with background and demonstrable expertise in numerical modelling
• Experience applying numerical methods to solve sets of differential equations in a coding language such as Python or MATLAB
• Experience using experimental data to tune and fit model parameters
• Experience on process validation
• Experience with knowledge sharing and training team members
• Experience with publication of academic papers and reports
• Strong organizational and project management skills
• Experience working in an interdisciplinary field and ability to gain knowledge of new areas and techniques
• Excellent communication and presentation skills, and the ability to convey complex information clearly
• Ability to work as part of a team at Heriot-Watt University and with collaborators in AI4
  
  Capture

• Strong knowledge of Python, including object-oriented programming and developing…