Innovation Placements

Scan have spent 30 years focusing on three things – technology, people, and how we bring them together. Be it PC gaming, professional graphics, video editing, music production or AI – Scan has a team of specialists ready and waiting to help. Our family of over 300 teammates live and breathe our 3XS philosophy of providing customers with the best Specification, Service and Satisfaction, which is reflected by the hundreds of awards Scan has won.

Due to our longstanding relationship with NVIDIA, the Scan AI business unit has grown to become one of the leading providers of bespoke custom Deep Learning & AI solutions in the UK. At the heart of this is our Scan AI Ecosystem. The Scan AI ecosystem has been created for every stage of the AI journey – whether you’re in early development of a model, in the midst of repeated training cycles or working on a complete inference deployment. Our AI experts, backed by our system design and build teams are able to offer bespoke solutions for AI innovation.

DiRAC will award one Innovation Placement in 2022 to explore with SCAN:

1) Price Recommender System
2) Virtual Warehouse
3) Product Recommender System

The placement will be with Scan UK. Please note each role has different technical skills that are required. Please read through each placement description and apply for the one that matches your skills and interests the most. You can apply for more than one placement; however, we expect that only one placement will be allocated this cycle.

You have to be working on research that falls within the STFC remit in order to qualify for the placement; however, you can be funded by other organisations besides STFC, as long as the subject area is identifiable as being in Particle Physics, Astronomy & Cosmology, Solar Physics and Planetary Science, Astro-particle Physics, and Nuclear Physics.

To check your eligibility, please contact Mark Wilkinson and Anushka Sharma: DiRAC-Placements@leicester.ac.uk

Information for candidates:

You must get your supervisor’s or PI’s permission before applying for this placement. Participation in the placement scheme is allowed under UKRI’s rules, but only with your supervisor/PI’s consent. We will do our best to be flexible; remote and part-time working can be arranged as long as the placement does not exceed 6 months.

This should be looked on as an opportunity to learn new skills and contribute outside of your research area while working with an AI Company deploying solutions into a sector of industry. The goal is to produce a predefined digital asset which could be a software solution, a report or indeed an innovative solution that has transferable reach across UKRI / Industry Sector and or form part of our library of AL/ML learning materials (WP 1.3).

The project builds on a 10-year programme of work in the Children and Young People’s Health Partnership (CYPHP).  CYPHP has delivered the building blocks for a Learning Health System that enables a data-driven approach to design and delivering a more effective model of children’s healthcare. Improved outcomes have been demonstrated, and the model is now commissioned as usual practice. This project will enable us to embed and improve our Learning Health System for children and is an important step towards spreading and scaling our approach to improving outcomes for children.

Click here for the job description