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For Companies At a Glance
- Tasks: Develop AI models for CO2 storage and fluid flow in porous media.
- Company: Heriot-Watt University is a leading institution focused on impactful research and innovation.
- Benefits: Enjoy 33 days of annual leave, flexible working options, and a supportive community.
- Why this job: Join a cutting-edge project with real-world impact and opportunities for professional growth.
- Qualifications: PhD in a relevant field and experience in deep learning and computational fluid dynamics required.
- Other info: Open to diverse applicants and promotes an inclusive work environment.
The predicted salary is between 37174 - 46735 £ per year.
Job Description
Role: Research Associate on Enabling CO2 storage using Artificial Intelligence
Grade and Salary: Grade 7, £37,174 – £46,735 per annum
FTE and working pattern: 1FTE, 35hrs per week, Monday – Friday
Contract: Fixed Term for 12 Months
Holiday Entitlement: 33 days annual leave plus 9 buildings closed days (and Christmas Eve when it falls on a weekday)
Purpose of Role
The successful candidate is expected to develop cutting edge deep learning models for multi-scale flow modelling of CO2 in subsurface reservoirs. Two aspects are of special interests (a) pore-to-core scale upscaling (b) upscaling of reactive flow processes at pore-scale. In addition, the successful candidates will contribute to a wide range of AI applications in subsurface flow modelling including (a) stochastic generation of porous media realizations using deep generative models (b) deep learning based property prediction using various architectures (c) Deep learning based proxy modelling with physics based losses and built-in model constrains (e) Efficient coupling of deep learning models to numerical solvers for hybrid CO2 flow modelling. The developed machine learning techniques will be open-sourced and be validated across a wide range of applications and on experimental data and direct numerical simulations generated by the project team.
Key Duties & Responsibilities
The successful candidate will be expected to undertake the following:
- Develop deep learning models for fluid flow in porous media.
- Disseminate research results in peer reviewed journals and interdisciplinary conferences.
- Publish open-source code repositories demonstrating all developed techniques and associated computational notebooks, blogs and presentation materials.
- Participate in regular project meetings with team members and project sponsors.
Essential & Desirable Criteria
Essential
- A PhD degree in computational science & engineering, applied mathematics, physics or in a related computational field (or close to successful completion).
- Prior experience in developing deep learning models using open-source libraries.
- Prior experience in computational fluid dynamics using open-source software packages.
- Strong track record of publications in high impact scientific journals.
- Working experience in modern software development techniques (version control, continuous integration, software testing, etc).
- Excellent verbal and written communication skills, and ability to write professional reports.
How to Apply
Applications can be submitted up to midnight (UK time) on Sunday 31st August 2025.
Please submit your CV & covering letter via the Heriot-Watt on-line recruitment.
We welcome and will consider flexible working patterns e.g., part-time working and job share options.
Heriot-Watt University is committed to securing equality of opportunity in employment and to the creation of an environment in which individuals are selected, trained, promoted, appraised, and otherwise treated on the sole basis of their relevant merits and abilities. Equality and diversity are all about maximising potential and creating a culture of inclusion for all.
Heriot-Watt University values diversity across our university community and welcomes applications from all sectors of society, particularly from underrepresented groups. For more information, please see our website https://www.hw.ac.uk/uk/services/equality-diversity.htm and also our award-winning work in Disability Inclusive Science Careers https://disc.hw.ac.uk/ .
Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by Heriot-Watt University.
About the Team
The School of Energy, Geoscience, Infrastructure and Society (EGIS) at Heriot-Watt university (HWU), Edinburgh, Scotland has an opening a 12 months PDRA position to work on the ECO-AI project (Enabling CO2 storage using Artificial Intelligence techniques). This post will be based at the Institute of GeoEnergy Engineering (IGE). Further details about ECO-AI project are available at the project webpage https://ai4netzero.github.io/ecoai_project/
About Heriot-Watt University
At Heriot-Watt we are passionate about our values and look to them to connect our people globally and to help us collaborate and celebrate our success through working together. Our research programmes can deliver real world impact which is achieved through the diversity of our international community and the recognition of creative talent that connects our global team.
Our flourishing community will give you the freedom to challenge and to bring your enterprising mind and to help our partners with solutions that can be applied now and in the future. Join us and Heriot Watt will provide you with a platform to thrive and work in a way that also helps you live your life in balance with well-being and inclusiveness at the heart of our global community. #J-18808-Ljbffr
Research Associate - Enabling CO2 Storage Using Artificial Intelligence employer: Heriot-Watt University
Contact Detail:
Heriot-Watt University Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate - Enabling CO2 Storage Using Artificial Intelligence
✨Tip Number 1
Familiarise yourself with the latest advancements in deep learning and computational fluid dynamics. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of AI and CO2 storage. Attend relevant conferences or webinars, and connect with researchers on platforms like LinkedIn to gain insights and potentially get referrals.
✨Tip Number 3
Showcase your experience with open-source libraries and software development techniques. Be prepared to discuss specific projects where you've applied these skills, as they are crucial for this role.
✨Tip Number 4
Prepare to discuss your publication history and how it relates to the job. Highlight any high-impact journals you've contributed to, as this demonstrates your capability and commitment to research excellence.
We think you need these skills to ace Research Associate - Enabling CO2 Storage Using Artificial Intelligence
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD in computational science or related fields, along with any relevant experience in developing deep learning models and computational fluid dynamics. Use keywords from the job description to align your skills with the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI applications in subsurface flow modelling. Discuss specific projects or experiences that demonstrate your expertise in deep learning and your ability to publish research results in high-impact journals.
Showcase Your Publications: If you have a strong track record of publications, mention them in your application. Include links or references to your work in high-impact scientific journals, as this will strengthen your candidacy and show your commitment to research.
Highlight Communication Skills: Since excellent verbal and written communication skills are essential for this role, provide examples of how you've effectively communicated complex ideas in previous projects, whether through reports, presentations, or collaborative meetings.
How to prepare for a job interview at Heriot-Watt University
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deep learning models and computational fluid dynamics. Bring examples of your previous work, especially any publications or projects that demonstrate your expertise in these areas.
✨Understand the Project Goals
Familiarise yourself with the ECO-AI project and its objectives. Being able to articulate how your skills align with the project's aims will show your genuine interest and understanding of the role.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, particularly in relation to AI applications in subsurface flow modelling. Think through potential challenges you might face in the role and how you would address them.
✨Communicate Clearly and Confidently
Since excellent verbal and written communication skills are essential, practice explaining complex concepts in a clear and concise manner. This will help you convey your ideas effectively during the interview.
