Thermodynamics Software Developer

This role will focus on enhancing the thermodynamic engine behind the client’s process simulation platform, developing and maintaining the models and algorithms used to simulate complex processes across oil & gas, LNG, refining, carbon capture, hydrogen, and other energy-related industries. The developer will work on scientific software development, primarily in C++ with Python, improving capabilities related to equations of state, phase behavior, distillation, electrolyte systems, property estimation, and oil characterization. This person will partner closely with software engineers, domain experts, and product teams to translate advanced thermodynamic concepts into reliable, high-performance simulation tools, while also supporting model validation, technical documentation, customer needs, and ongoing innovation within the platform. The ideal candidate brings a strong foundation in computational thermodynamics, enjoys solving complex technical challenges, and can bridge the gap between research-level methodologies and practical software applications.

• Master’s or PhD in a related technical field (Chemical Engineering, Chemistry, Applied Mathematics, etc.) or 5-10+ years of hands-on experience in thermodynamics, process simulation, or scientific software development.
• Experience developing scientific software focused on fluid modeling, thermodynamics, or process simulation
• Hands-on experience with one or more of the following: Equations of State (EOS) Phase equilibrium calculations Activity coefficient models Property estimation methods Electrolyte systems Oil characterization
• Strong background in numerical methods and thermodynamic calculations
• Proficiency in C++ and/or Python for scientific or engineering software development
• Experience designing, developing, testing, validating, and documenting software solutions
• Ability to work independently and collaborate effectively in a team environment
• Adaptability to learn new technologies, programming languages, and modeling approaches
• Experience with electrolyte thermodynamics and/or distillation algorithms
• Experience automating large-scale thermodynamic, numerical, or simulation workflows
• Experience using or developing commercial process simulation software (Symmetry, Aspen, HYSYS, ProMax, UniSim, etc.)
• Background in data science or machine learning
• Research or industry experience involving advanced thermodynamic modeling and simulation