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- Tasks: Collaborate on asphaltene fluid modelling and develop innovative workflows.
- Company: Join SLB, a global leader in energy innovation for a balanced planet.
- Benefits: Gain hands-on experience, mentorship, and contribute to real-world energy solutions.
- Why this job: Make an impact in the energy sector while developing your technical skills.
- Qualifications: Pursuing a Masters in Chemical Engineering or related field with programming skills.
- Other info: Inclusive workplace with opportunities for growth and learning.
Job Description
Scientific Software Engineer Intern (3 months) – Starting Summer 2026
Project Title: Asphaltene Fluid Modeling and Equation of State Tuning
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 company website
Location:
Abingdon, Oxfordshire
Description & Scope:
Classical thermodynamics forms the foundation for modeling a wide range of engineering applications, particularly in the oil and gas industry. The behavior of fluid and solid systems is often described using Equation of States (EoS), which capture the relationship between pressure, volume, temperature and composition. For pure components, well-established EoS models exists, calibrated using laboratory data, thereby reducing the need for extensive tuning in practical applications.
However, modeling the behavior of mixtures, particularly hydrocarbon mixtures, presents a significant challenge. The presence of numerous components, including isomers, makes it impractical to model each component individually. This complexity is further amplified in systems involving asphaltenes – highly complex and poorly characterized fractions of crude oil.
To address these challenges, techniques such as lumping and tuning are employed to simplify real-component systems into pseudo-component mixtures. These approaches aim to retain the key thermodynamic behaviours of the system while significantly reducing computational costs. In this context, we can write the tuning as a data-assimilation problem and solve it by applying different methods.
This internship focuses on tackling the tunning problem for asphaltene modeling using various EoS formulations, including Peng-Robinson, Soave-Redlich-Kwong and Cubic Plus Association (CPA). The goal is to develop a robust workflow that convert asphaltene PVT laboratory data into EoS inputs applicable to real-world oil industry scenarios.
Responsibilities
As part of this internship, the candidate will collaborate closely with the Intersect Physics team and undertake the following responsibilities:
- Literature review: conduct an in-depth review of the state-of-the-art in asphaltene modeling, PVT laboratory data interpretation, and Equation of State tuning techniques
- Data tuning: implement and apply tuning methodologies to real asphaltene PVT laboratory datasets
- Workflow development: design and document a systematic workflow for converting asphaltene PVT laboratory data into EoS inputs
- Validation and comparison: evaluate and compare the performance of different EoS models, identifying strengths and limitations for each
- Manuscript preparation: prepare a detailed manuscript summarizing the workflow, methodology, and key findings. The manuscript will serve as a basis for potential submission to a research journal
Qualifications :
- Studying a Masters in Chemical Engineering, Fluid Modeling, Applied Physics or a related discipline
- Thermodynamics and fluid modelling
- Data analysis
- Programming (Python)
- Scientific documentation
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.
Scientific Software Engineer Intern (3 months) employer: Schlumberger
Contact Detail:
Schlumberger Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Scientific Software Engineer Intern (3 months)
✨Tip Number 1
Network like a pro! Reach out to current or former employees at SLB on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into asphaltene modeling and EoS tuning. Show us you’re not just interested in the role but passionate about the challenges we face in energy innovation.
✨Tip Number 3
Practice your coding skills in Python! We love seeing candidates who can demonstrate their programming prowess, especially when it comes to data analysis and workflow development.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our mission for a balanced planet.
We think you need these skills to ace Scientific Software Engineer Intern (3 months)
Some tips for your application 🫡
Show Your Passion for Energy Innovation: When writing your application, let us see your enthusiasm for energy innovation and how it aligns with our mission. Share any relevant projects or experiences that highlight your interest in tackling the challenges of the fossil fuel industry and contributing to a balanced planet.
Highlight Relevant Skills: Make sure to showcase your skills in thermodynamics, fluid modelling, and programming (especially Python). We want to know how your academic background and technical abilities make you a great fit for this internship, so don’t hold back on the details!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your experiences and qualifications. We appreciate well-structured applications that are easy to read, so avoid jargon unless it's necessary.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, you’ll find all the information you need about the position there!
How to prepare for a job interview at Schlumberger
✨Know Your Thermodynamics
Brush up on your thermodynamics and fluid modelling concepts. Be ready to discuss how these principles apply to asphaltene modeling and Equation of State tuning. Showing a solid understanding will impress the interviewers at SLB.
✨Show Off Your Programming Skills
Since programming in Python is key for this role, prepare to talk about your experience with coding. Bring examples of projects or coursework where you've used Python for data analysis or modelling. This will demonstrate your technical capabilities.
✨Prepare for Technical Questions
Expect some technical questions related to the job description, especially around EoS models and data tuning methodologies. Practise explaining complex concepts in simple terms, as this shows you can communicate effectively with both technical and non-technical audiences.
✨Have Questions Ready
Interviews are a two-way street! Prepare thoughtful questions about the team, the projects you'll be working on, and SLB's approach to energy innovation. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
