Student Placement - Machine Learning Technician
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Employment type:
Full time
Experience required:
Intermediate
Salary
Salary not provided
About the company:
Tokamak Energy is a private company accelerating the development of fusion power.
Fusion – the energy source that powers the sun – is globally accepted as the best way to generate plentiful, safe, secure and clean energy. The tokamak is the most heavily researched and best understood of all the different paths to fusion.
It is now acknowledged that the spherical tokamak design offers the smallest and most cost-effective solution. This is our solution. Yet there are many complex engineering challenges that need to be overcome for demonstration and commercialisation of this technology.
Our team of world-class fusion scientists and magnet engineers is tackling these challenges to develop efficient and affordable fusion power. Our unique approach is centred on rapid innovation using the latest materials and technology – but building on decades of scientific research and experience. This strategy gives us – and the world – a faster way to fusion.
Once fusion electricity is achieved, our scalable technology could be rolled out across the world as a solution to one of humanity’s greatest challenges: clean and sustainable energy for all.
Tokamak Energy are pleased to be offering a number of Summer placement opportunities to undergraduates who are studying a relevant degree and seeking experience within a commercial Fusion organisation. Our Summer placements offer a fantastic opportunity to work with highly talented individuals and teams, focusing on a focused project or series of small projects and tasks to support our mission and goals.
This opportunity will not only be a great way to apply some of your learnings from your studies, but also be part of a commercial Fusion working environment combining R&D with Programme delivery and learning to work in a collaborative and innovative workplace. You will have the opportunity to apply your skills and abilities within a variety of areas including communication, teamwork, project management and much more!
Overview of the role
With irradiated materials, there is often a sparsity of property data because of the significant expense, time scale, and complexity of irradiation testing and post-irradiation characterization. This role is aimed at developing machine learning tools that can be used to either enhance the collection of data from open literature or improve the analyse of sparse datasets.
In this role, you will:
· Write machine learning algorithms for data scrapping or advanced data analysis.
· Train and test machine learning algorithms with materials property data.
· Develop workflows to interface with the TE materials database.
· Develop standards for the evaluation of data quality.
Requirements
· Required: knowledge of programming language(s) useful to machine learning such as Python.
· Required: knowledge of algorithms for machine learning such as Gaussian processes, gradient boosting, K-means, random forest, etc.
· Required: communicating and relating with others (oral/written)
· Valued: experience with database structures.
· Valued: understanding of thermo-mechanical, electro-magnetic, neutronic, and irradiated material properties.
Benefits
- Fusion Industry experience.
- Be part of a dynamic team and collaborate with experts in field.
- 5 days holiday.
- Competitive pay.
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