Career Opportunities: Simulation Technology Developer (18327)

Requisition ID 18327 - Posted 

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SLB is seeking a Simulation Technology Developer to join our Dynamics team in Calgary, Alberta. In this role, you will help develop and improve advanced simulation software used to model transient pressure-flow behavior across energy systems, including oil and gas, LNG, refining, carbon capture, hydrogen, and other energy transition applications. The successful candidate will contribute to the full software development lifecycle, including algorithm design, numerical implementation, testing, validation, documentation, and deployment. We are looking for someone with a strong foundation in numerical methods, scientific computing, and software development who enjoys solving complex technical challenges. Success in this role requires curiosity, initiative, and a willingness to continuously learn and explore new technologies, numerical techniques, and approaches.

Roles and Responsibilities

• Develop and improve numerical solvers and simulation capabilities for transient pressure-flow networks and dynamic energy systems.
• Design, implement, test, validate, and document software features across the full product development lifecycle.
• Build clean, maintainable, and high-performance code, primarily using C++ and Python.
• Work with stiff DAE/ODE systems, numerical integration methods, and computational techniques to ensure simulation accuracy, stability, and performance.
• Collaborate with domain experts, software developers, testers, and customers to deliver reliable simulation solutions.
• Develop, maintain, and enhance core simulation engine components and numerical solvers to improve performance, stability, and simulation accuracy.
• Support applications such as design studies, control strategy validation, start-up and shutdown analysis, flow assurance, safety analysis, and operator training.
• Contribute to technical documentation, customer support, and occasional consulting activities.
• Stay current with new technologies, numerical techniques, and scientific computing practices to support continuous improvement.

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