National Platform for RTPs on AI for Science and Engineering (NPRAISE)

AI is one of the key technologies of this century, with benefits permeating every aspect of our life. If the full potential of AI can be leveraged to accelerate science and engineering, the resulting impact will be disruptive and transformative. The benefits will be felt in our everyday life: from better understanding of how viruses function, to accelerated design of drugs to the design of greener infrastructures, through to solving the mystery of our existence. To achieve this, we need research technical professionals (RTPs) able to apply their knowledge of AI to advance science and engineering, so that humanity can make progress in tackling society's urgent and grand challenges.

Due to the break-neck speed in the development and expansion of AI, education and training opportunities in AI have not been developed fast enough to be able to satisfy the demand for a suitably skilled workforce. The global shortage of AI skills is hindering its transformative potential in many fields, including scientific research. AI for science and engineering requires RTPs with different blends of experience across high-resolution simulation techniques, science domains, large scale computing and data science. In order to bridge the skills gap, a sizeable national-level approach is imperative. This needs to be built with an interdisciplinary approach at its core, as traditional methods involving groups or organisations with deep but narrow expertise are inadequate for developing the blend of skills and experience needed for addressing scientific and engineering challenges at scale.

This proposal aims to establish a national and interdisciplinary platform that nurtures a community of RTPs who specialise in developing and applying AI to scientific and engineering challenges. This will include ongoing training, support, and development opportunities, and advocacy for the role of RTPs. This National Platform for RTPs on AI for Science and Engineering (NPRAISE) will be built on solid foundations provided by well-established programmes within STFC Scientific Computing: the Scientific Machine Learning (SciML) group will provide the AI training and supervision; the Computational Science Centre for Research Communities (CoSeC) and the Ada Lovelace Centre (ALC) will offer a rich and varied portfolio of projects that RTPs will work on to gain practical experience in applying AI skills to real-world, large-scale science and engineering. Opportunities offered by partner organisations (e.g., DOE National Labs in the US) will enrich the RTP experience and enable knowledge exchange at the national and international level. The wider STFC Scientific Computing environment will complement the AI and science and engineering training with training on other computing skills (e.g., data management) and other practical skills with the aim to produce a well-rounded cohort of RTPs ready to embark successfully in careers in academia and industry.

Recognising the significance of training RTPs, and the alignment of NPRAISE's objectives with STFC's priorities, STFC Scientific Computing will be waiving all overheads associated with the project. As such, all costs of NPRAISE are purely directly incurred, enabling us to train a minimum of 16 RTPs over four years, maximising the potential of the funding.