Software Engineer Intern (12 months)

SLB; Cambridge; On-site; GBP 21,000 - 26,000; Full time

Job summary

SLB Cambridge Research invites applications for a Software Engineer Intern (12 months) starting Summer 2027. You will join the Systems and Processes team working on machine learning for next-generation energy applications.

In this role you will apply reinforcement learning, optimization, and Bayesian methods to model processes, scope your own project with guidance, and present results to colleagues and stakeholders.

Qualifications

• Pursuing a bachelor’s degree in CS/AI/Physics or related field.
• Programming skills in Python or C/C++.
• Interest in research and AI/ML.
• Interest in the energy sector.

Responsibilities

• Bring your computer science/software background to solve challenges at SLB
• Engage with real problems we are trying to solve
• Experiment with CS, ML and AI techniques beyond your current background
• Scope your own project(s) with support and guidance from us
• Sporadically present progress and results to colleagues, other interns, and stakeholders.

Skills

Python

C/C++

Research interest

AI/ML interest

Energy industry interest

Education

Bachelor's degree in Computer Science, AI, Physics or related

Job description

Job Title

Software Engineer Intern (12 months) - Starting Summer 2027

Project Title

Machine learning for future energy applications

About SLB

We are a global technology company, driving energy innovation for a balanced planet. At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that has been our mission for 100 years. We are facing the world’s greatest balancing act- how to simultaneously reduce emissions and meet the world’s growing energy demands. We’re working on that answer. Every day, a step closer. Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It’s what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet. Our purpose: Together, we create amazing technology that unlocks access to energy for the benefit of all. You can find out more about us on https://www.slb.com/who-we-are

Location

Cambridge, UK

SLB Cambridge Research (SCR) is part of SLB’s global network of research and engineering centres. SCR is a dynamic, multidisciplinary environment with state-of-the-art research and computing facilities. We work on applied research projects in the physical sciences to meet the current and future challenges of the industry.

Description & Scope

You will join the Systems and Processes team. We investigate how machine learning, optimization, and AI can be used to understand next-generation energy and thermal management systems. We use techniques like reinforcement learning, multi-objective optimization, and Bayesian methods to model the processes involved in bringing new energy technologies to market, manage uncertainty, and optimize decisions.

Responsibilities

• Bring your computer science/software background to solve challenges at SLB
• Engage with real problems we are trying to solve
• Experiment with computer science, machine learning and AI techniques beyond your current background
• Scope your own project(s) with support and guidance from us
• Sporadically present progress and results to colleagues, other interns, and stakeholders.

You Will Learn

• A great deal about industrial/commercial research
• How to scope and manage your own time and project(s)
• Presentation skills (for different audiences)
• Computer science, machine learning, and AI methods beyond your current course.

Qualifications

• Studying Bachelors in Computer Science, AI, Physics or a related discipline
• Software development skills in at least one of Python, C/C++
• Interest in research
• Interest in AI, machine learning, and related areas
• Interest in the energy industry

SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.

The recruiting process and the position can be adapted to fit most disabilities, please do not hesitate to mention this when applying.