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Student Placement - Machine Learning Technician

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Tokamak Energy

17d ago

🚀 Placement Program


AI generated summary

  • You must know Python, machine learning algorithms, database structures, and understand physics principles for this placement at Tokamak Energy.
  • You will write and test machine learning algorithms, develop workflows, and establish data quality standards for materials property data at Tokamak Energy.

Placement Program



  • 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.


  • 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.

Education requirements

Currently Studying

Area of Responsibilities



  • 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.


Work type

Full time

Work mode





  • Fusion Industry experience.
  • Be part of a dynamic team and collaborate with experts in field.
  • 5 days holiday.
  • Competitive pay.