Fluid and Heat Transfer Simulation Engineer-II

About POWERTECH

POWERTECH is a center of excellence for propulsion technologies, specializing in the design, engineering, and manufacturing of combustion engines, expendable turbojet engines, and turbofan engines for a wide range of aerospace, defence, and autonomous applications, including fixed- and rotary-wing UAVs and other advanced platforms.

Position Overview
Powertech’s Technology Development Team is seeking a Fluid and Heat Transfer Simulation Engineer-II to support the research, development, and maturation of advanced propulsion systems for military applications. This role focuses on high-fidelity simulation of combustion aerodynamics and heat transfer for low-speed and high-speed combustion systems, supporting technology advancement from TRL 1 through TRL 7.
The position requires deep expertise in complex CFD, LES, thermo-fluids, and Multiphysics modelling, with a strong emphasis on combustion system optimization, cooling reduction, physics-based understanding, and workflow development. The engineer will evaluate novel combustor concepts and apply innovative and data-driven simulation techniques to advance next-generation fluid systems.

Key Responsibilities

Simulation & Analysis

• Conduct advanced CFD simulations for combustion aerodynamics and heat transfer, including low-speed and high-speed combustion regimes
• Perform steady and unsteady simulations, including complex Large Eddy Simulations (LES) using STAR-CCM+ and ANSYS FLUENT
• Execute thermoacoustic analyses to assess combustion instability and system coupling
• Perform conjugate heat transfer (CHT) analyses to evaluate thermal loads, cooling effectiveness, and component durability
• Support turbomachinery and aerodynamic simulations using high-fidelity numerical methods

Combustion System Development

• Conduct simulations and analysis for combustor development, including cooling strategies, heat transfer, and CFD-based combustion modelling
• Optimize combustion systems to improve performance, efficiency, and reduce cooling requirements
• Perform deep physics-based investigations of combustion, flow structures, heat transfer, and acoustic interactions
• Evaluate new combustor concepts and innovative propulsion technologies, applying analytical and numerical method

Design, Validation & Collaboration

• Apply numerical design and optimization tools for fluid, combustion, and turbomachinery systems
• Develop and standardize robust workflows for LES and advanced thermo-fluid simulations
• Collaborate closely with aerodynamics, thermal systems, structures, materials, and design teams to define boundary conditions, interfaces, and performance criteria

Technology Development

• Advance internal modelling strategies and validation methodologies for complex physical phenomena in propulsion combustion systems
• Support propulsion technology maturation across TRL 1–7, from fundamental research through subsystem and prototype demonstration

Contribute to technical reports, design reviews, proposals, and internal technology roadmaps

Required Qualifications

• PhD or MS in Aerospace Engineering, Mechanical Engineering, or a related field
• 3–7 years of relevant industry or research experience in combustion, heat transfer, CFD, or propulsion systems
• Strong experience with complex CFD calculations, including steady and unsteady flows
• Demonstrated expertise in LES modelling, including setup, execution, and post-processing
• Proficiency with STAR-CCM+ and ANSYS FLUENT
• Experience with thermoacoustic and conjugate heat transfer (CHT) analysis
• Solid understanding of combustion aerodynamics, thermo-fluids, and heat transfer physics
• Ability to develop repeatable, automated simulation workflows

Preferred Qualifications

• Experience with military or defence propulsion systems
• Familiarity with Open FOAM, custom UNIX/Linux-based workflows, and scripting or programming for simulation automation and data analysis
• Experience working in low-TRL research environments
• Background in combustion system optimization, thermal management, and cooling design
• Experience applying data-driven, machine-learning, or reduced-order modeling techniques
• Experience supporting experimental rig testing and model validation

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