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🚀 Internship

Undergraduate Placement - Data Scientist (Nuclear Threat Reduction)

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5d ago

🚀 Placement Program


🤑 £20.5K

AI generated summary

  • The candidate should possess a growth mindset, be curious and innovative, have resilience, and be a dependable team worker.
  • The undergraduate placement as a Data Scientist at AWE involves utilizing data science techniques to analyze and understand data related to nuclear threat reduction, particularly through the fusion of information from multiple sources. The candidate will work within a multidisciplinary team, applying data science techniques to contribute to the CTBT analysis and enhance event assessment.

Placement Program



Rolling basis


  • Nuclear Threat Reduction (NTR) supports the Government on a variety of national security issues related to radiological and nuclear materials. The work varies from fundamental and novel research to applied development of technology demonstrators. Application areas within NTR include detection of nuclear and radiological material, nuclear forensics, international treaty monitoring and verification.  
  • The Comprehensive Nuclear-Test-Ban-Treaty (CTBT) “bans nuclear explosions by everyone, everywhere: on the Earth’s surface, in the atmosphere, underwater and underground.”  We support the Ministry of Defence in underpinning the CTBT by providing technical advice on the verification regime.  The CTBT uses four complementary verification methods; seismic, infrasound, hydroacoustic and the detection of radionuclides within the International Monitoring System.
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  • You will possess the following traits and qualities: 
  • Growth Mindset; You’re full of grit and determination. Clear where you are going and how you will get there. 
  • Curious; you’re a person who loves to think outside the box. (You’re a person who loves to take the box apart!). 
  • Innovative; you’re open to learning about new technologies and ground-breaking ideas. 
  • Resilience; you’re an advocate of ‘speaking up’ for yourself and others openly and constructively. 
  • Team Worker; you’re dependable and reliable.  You’re interested in collaborating with and supporting others. 
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Education requirements


Area of Responsibilities



  • This project aims to investigate the use of data science techniques to contribute to the analysis and understanding of the data that is gathered in support of the CTBT. Of particular interest are techniques to ‘fuse’ information from multiple data sources to improve the overall assessment of events of interest. Joining the team as an undergraduate student, you will gain experience and knowledge of working within a multidisciplinary team of scientists applying data science techniques to the NTR mission.
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Work type

Full time

Work mode





20500 GBP


  • A market leading contributory pension scheme  
  • Generous holiday entitlement  
  • Excellent work/life balance   
  • 9-day working fortnight. This means you get every other Friday off work.  
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Rolling basis