eightfold
Process Simulation Software Developer
SLB
Calgary, CAN
Full-time
Entry
Onsite
Discovered 1 weeks ago
C++PythonAImachine learning
Free
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Roles and Responsibilities
- Develop and improve simulation algorithms, process models, and numerical methods used for time-dependent (dynamic/transient) process systems.
- Design, implement, test, validate, and document simulation capabilities across the full product development lifecycle.
- Build clean, maintainable, and high-performance code primarily in C++ and Python, including supporting tools and workflows.
- Apply numerical methods with attention to stability, accuracy, and computational performance for complex engineering simulations.
- Collaborate with domain experts, software developers, testers, and customers to deliver reliable simulation solutions.
- Identify and address performance, stability, or accuracy issues in simulation models, solvers, and workflows.
- Explore and apply AI, machine learning, or data-driven techniques (where valuable) to enhance simulation workflows and productivity.
Qualifications and Experience
- Bachelor’s, Master’s, or PhD in Chemical or Process Engineering is strongly preferred. Degrees in Applied Mathematics, Computer Science, or a closely related field will also be considered.
- Hands-on experience developing numerical algorithms, numerical solvers, process models, simulation engines, or scientific computing applications. Experience developing underlying simulation technology is preferred over experience focused primarily on using commercial simulation software.
- Strong programming skills in C++ and Python applied to numerical, computational, or engineering problems.
- Strong understanding of process engineering principles, process modeling, and process simulation.
- Understanding of numerical methods, mathematical modeling, numerical stability, and accuracy.
- Experience with dynamic/transient simulation, pressure-flow networks, thermodynamic modeling, unit operations, or related process simulation technologies is an asset.
- Interest or experience in AI/ML or data-driven modeling/optimization is an asset; experience applying AI/ML to engineering, simulation, or scientific computing problems is particularly valuable.
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