STFC - ISIS - Machine Learning for Accelerator Control Systems Graduate
The Science and Technology Facilities Council (STFC) is one of Europe’s largest research organisations. We’re trusted to support, enable and undertake pioneering projects in an amazing diversity of fields. Through world-class facilities and people, we’re driving ground-breaking advances in science, technology and Engineering.
STFC is one of nine organisations that have been brought together to create UK Research and Innovation (UKRI); a new organisation with a vision to ensure the UK maintains its world-leading position in research and innovation.
Our graduates join us in a permanent position, starting a real job from day one. Graduates enjoy two years of formal soft skills together with technical training and development, as well as a direct route to professional accreditation. STFC graduates have the opportunity to build on their degree, taking their understanding, knowledge and skills to a new level in a dynamic, creative,collaborative culture.
STFC consists of several distinct departments which each focus on a different specialism within science, technology, innovation and support, yet work together to achieve STFC’s grand ambitions. Different departments may look for graduates with similar skills, so you should consider which role/s are most suitable to you, and apply for up to two of these.
The ISIS Neutron Source
ISIS is a neutron source located at the Rutherford Appleton Laboratory in the UK used for cutting-edge research in material and biological sciences. Large quantities of diagnostic and control data is generated during the operation of the ion-source, linear accelerator and synchrotron. The Accelerator Controls section is responsible for the collection and dissemination of data related to the control and status of the accelerators.
Summary of Key Duties & Responsibilities
Machine learning is a technology which has not yet seen widespread use at the ISIS accelerators. With the large quantity of live and historic data available to the Accelerator Controls section there is considerable scope to use machine learning techniques to improve our operations. This could range from detection of problematic anomalies, through to system modelling, and even control and tuning of the accelerators.
The successful candidate will be required to:
- Design and implement machine learning software with the purpose of improving efficiency and availability of the ISIS accelerators. For example, improving the lifetimes of the Penning ion-sources.This will require working with many other scientists and engineers across the ISIS accelerators
- Drive the adoption of software development methodologies within the accelerator controls section, e.g. unit testing,test-driven development, continuous integration/continuous development, and DevOps best practices
- Upgrade legacy applications within the ISIS controls system, especially in light of the previous two requirements
- Assist with keeping the ISIS accelerator controls system operational. This includes providing out of hours on-call support, bug fixing and integration of new features to existing applications.
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