Industrial Research Engineer

Industrial Research Engineer – Probabilistic Computing for Air Traffic Management 

Overview 

We’re excited to offer a unique 10‑week industrial research placement working at the frontier of probabilistic computing, modelling, and aviation. In this project, you’ll help shape next‑generation computational models for UK Air Traffic Management (ATM), contributing directly to a pioneering collaboration between Quantum Dice and NATS (UK Air Traffic Control). 

You’ll join a team operating at the intersection of quantum technologies, security and high‑integrity real‑world systems — an environment where rigorous engineering meets ambitious innovation 

About Quantum Dice 

Quantum Dice is a fast‑growing deep‑tech company building probabilistic technologies. Our work combines quantum hardware, advanced computation, and real‑world critical applications. We operate in a highly collaborative, engineering‑driven environment where you’ll work closely with experts across research, modelling, security, and systems development. 

This placement offers exposure to a cutting‑edge sector and the opportunity to make a meaningful contribution to a project that influences how next‑generation ATM systems are modelled and understood. 

What You’ll Be Doing 

During your 10‑week placement, you will: 

• Develop advanced probabilistic and computational models for Air Traffic Management challenges. 


• Work with Quantum Dice and NATS domain specialists to identify key modelling, uncertainty, and computational constraints in operational ATM environments. 


• Prototype and benchmark new modelling approaches using probabilistic programming techniques, simulation frameworks, and Python‑based scientific ecosystems. 


• Evaluate models against baseline methods, assessing accuracy, uncertainty characterisation, robustness, and computational performance. 


• Communicate findings clearly through presentations, discussions, and collaboration sessions with technical stakeholders. 


• Produce clear technical documentation, experiment records, and a polished final report summarising your outcomes. 

This is an in‑person role based in Oxford, UK, with occasional on‑site stakeholder interactions. 

Who You Are 

• MSc or PhD student in Computer Science, Engineering, Applied Mathematics, or a related discipline — or equivalent industry experience. 


• 1–2 years’ experience working in an applied technical or research environment. 


• Strong grounding in probability, statistics, and stochastic processes. 


• Able to independently tackle analytical, research‑driven technical work. 


• Curious, proactive, and excited to explore unfamiliar technical areas. 


• A strong collaborator with clear written and verbal communication skills. 

Experience With 

• Software engineering tools (Git, collaborative workflows). 


• Core scientific Python libraries. 


• Technical writing and documentation for technical and non‑technical audiences. 


• At least one of the following:  
  
  
  
  • Probabilistic computing or Ising machines 
  
  
  • Operations research 
  
  
  • Optimisation techniques 
  
  
  • Simulation methods (e.g., Monte Carlo) 
  
  
  • Machine Learning 
  
  
  
  

Desirable 

• Experience in aviation, ATM, or other safety‑critical domains. 


• Awareness of functional safety or security principles. 


• Experience with modelling or simulation codebases. 


• Understanding of quantum technologies. 

Even if you don’t meet all criteria, if you feel you can add value, we strongly encourage you to apply. 

Why Join Us 

• Work on a genuinely novel project with real-world impact for both Quantum Dice and NATS. 


• Engage directly with domain experts, senior stakeholders, and cutting‑edge engineering teams. 


• Influence an emerging research direction within a growing deep‑tech company. 

The Perks 

• Competitive salary (pro‑rated for the 10‑week placement). 


• High‑impact project with strong mentorship and technical visibility. 


• Opportunities to engage with senior engineering and research teams across both organisations. 

Application Process 

• Send us your CV and a short paragraph outlining your relevant experience and what you hope to contribute to this collaboration. 


• Two‑phase interview process: individual technical interview followed by a panel session with project leads. 

Please note this placement is only open to applicants who are eligible to work in the UK. No sponsorship will be offered.