Are you a data scientist keen to apply ML/AI techniques to enhance your data analysis tasks?
Are you a research software or data engineering professional working within industry or academia, and keen to learn more about application of AI/ML in science or engineering?
Would you like to see first-hand how AI/ML is supporting greater scientific discoveries?
The opportunity
If you have answered yes to any of these questions, then we are delighted to announce further exciting opportunities to develop your AI/ML skills and enhance your knowledge on applied AI. As part of the ExCALIBUR Blueprinting for AI at Exascale project and in response to popular demand, our Scientific Machine learning Group (SciML) within Scientific Computing at STFC are now offering part-time placement opportunities to spend time with our team and learn from the experts to develop your practical and technical skills in AI for Science application.
What will the placement involve?
SciML will provide coaching on a broad range of machine learning skills as follows:
- Basic carpentry skills covering ML for Science, platforms for AI and computational science, and research data engineering/management.
- Computational Science and AI: Surrogate models for simulations, generative models for computational sciences, and physics informed neural networks (PINNs), and
- Advanced AI for Science: AI patterns for science and engineering, AI benchmarking, latent-space modelling, bridging the gap between experimental and simulated datasets, HPC-AI converged models, AI at the Edge, data denoising, domain-specific ML models, and large-language models (LLMs) for science.
How does the placement work?
- It is flexible and part-time to suit your commitments.
- It is non-contractual with no transfer of employment to STFC as the host organisation.
- Reasonable travel expenses to the host location: STFC, Rutherford Appleton Laboratory, Didcot, OX11 0QX.
- Placements available for 3 months.
- You will have access to STFC systems to conduct day-to-day work within the SciML group.
In all cases, we welcome a conversation to discuss how to work around your other commitments.
Essential skills required for this placement:
- Currently working within the discipline of Data Science / Engineering role.
- Proven programming skills on Python and Linux, and
- Strong technical background in computer science or electrical engineering or a relevant area, e.g., mathematics, materials sciences, physics, chemistry, life sciences or computationally driven areas of science (including environmental sciences) or equivalent experience in other areas.
How to apply?
Please submit your expression of interest form by 5pm, 30th August 2024
If you would like to discuss with us any aspect of this placement, please contact us at
These placements are funded through an EPSRC’s funded project, ‘Blueprinting AI for Science at Exascale (BASE-II).’ For further information, please see https://ai4science-at-scale.ac.uk/