Key Responsibilities
· Plan, execute and document CFD studies for turbocharger components (compressor wheel, turbine wheel, volutes, VTG, bearing housing flow) including compressible, transient, and conjugate heat transfer cases.
· Select appropriate physical models (RANS/URANS/SBES/LES, turbulence, sliding mesh/mixing plane) and verify grid/time-step independence with sound y+ management and GCI methodology.
· Set up automated pre/solve/post pipelines (Python/bash), parameter sweeps and design-of-experiments; maintain version-controlled templates and reports.
· Correlate simulation results to hot-gas-stand measurements; drive root-cause analyses and propose design countermeasures.
· Perform optimization against efficiency, pressure ratio, surge margin and NVH constraints across multiple operating points.
· Support forced response analysis / structural risk assessment through CFD→FEA coupling in collaboration with structural analysis.
· Collaborate cross-functionally with platform owners, validation and application teams; contribute to internal best-practice guides and knowledge bases.
· Communicate results clearly to technical and non-technical audiences, including gate reviews and customer meetings as required.
Required Qualifications
· Master’s degree (or higher) in Mechanical/Aerospace Engineering or similar, with focus on turbomachinery/fluids.
· 3+ years of hands-on CFD experience for rotating machinery with compressible aerodynamics (shock/expansion, tip leakage, stall/choke).
· Proficiency with Ansys CFX/Fluent and/or STAR-CCM+ and/or OpenFoam; strong meshing skills, CAD interfaces (Creo/NX/CATIA).
· Scripting/automation in Python; batch/scheduler usage; Git-based version control.
· Demonstrated test correlation experience (hot-gas-stand/compressor & turbine map), uncertainty analysis, and robust reporting.
· Professional English communication skills (written and verbal).
Preferred Qualifications
· Experience with wheel and volute optimization
· Background in turbo integration, thermal management and materials
· Acoustics (broadband/tonal) and 1D–3D co-simulation for pulsating turbine inflow.
· Exposure to forced response workflows (CFD→FEA) and durability risk screening.
· Data-driven methods/ML surrogates for rapid map prediction and design space exploration.
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