Senior Engineer / Scientist - CMP Fundamentals, Modeling & Simulation

Qnity Electronics, Inc.

• $110K — $130K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's or Ph.D. in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, or related discipline.
  • Less than 5 years of industrial experience in applying scientific and engineering principles.
  • Demonstrated experience in mathematical modeling and experimental method development.
  • Strong background in computational modeling and data analysis.
  • Proficiency in MATLAB, Python, or similar technical computing environments.
  • Expert knowledge in transport phenomena, fluid mechanics, tribology, and surface characterization.
  • Strong interpersonal skills for collaboration with multidisciplinary teams.

Responsibilities

  • Provide technical leadership and solve scientific problems related to CMP fundamentals.
  • Lead investigations involving complex material behavior and process interactions.
  • Apply rigorous methodologies to tackle short- and long-term technological challenges.
  • Collaborate with research and product development teams to drive innovation.
  • Build physics-based simulation models and optimize their efficiency for development use.
  • Design experiments for validation and develop calibration methods with team members.
  • Correlate simulation outcomes with laboratory data and real-world customer results.

Benefits

  • Comprehensive pay and benefits package.
  • Opportunities for collaboration with internal and external technical experts.
  • Access to mentorship programs for professional growth.
  • A work environment that fosters innovation and interdisciplinary collaboration.
Full Job Description
Key Responsibilities:

  • Technical Leadership & Scientific Problem Solving
  • Lead complex technical investigations requiring deep understanding of CMP fundamentals, material behavior, and process interactions.
  • Apply rigorous science-based methodologies to solve short- and long-term technology challenges.
  • Partner with research, applications, product development, manufacturing, and data science teams to accelerate innovation.


Simulation Reliability, Validation & Capability Development :

  • Build complex, physics-based simulation models from first principles
  • Optimize model architecture, meshing strategy, solver settings, and runtime efficiency to enable reliable and practical use in product development.
  • Evaluate model assumptions, governing equations, constitutive relationships, material models, and boundary conditions to ensure simulations accurately represent physical behavior.
  • Verify model accuracy through numerical checks, experimental validation, calibration, and uncertainty assessment.


Experimental Research & Characterization :

  • Design validation experiments in partnership with scientists and engineers.
  • Develop methods for model calibration and parameter identification.
  • Leverage characterization tools and experimental resources to improve understanding of polishing mechanisms.
  • Serve as an internal expert in texture characterization, material behavior, and performance-driving mechanisms.
  • Correlate simulation results with laboratory observations and customer outcomes.


CMP Fundamentals Development :

  • Build fundamental understanding of interactions between:
    • Pad materials and structure
    • Solid Mechanics
    • Fluid mechanics
    • Contact mechanics
    • Tribology and wear
    • Semiconductor process operating conditions
    • Translate scientific understanding into actionable design guidance and product development recommendations.


Mentorship & Collaboration:

  • Develop and manage collaborations with internal and external technical experts.
  • Communicate findings through technical reports, presentations, customer interactions, patents, and publications.


Required Qualifications:

  • Master's degree or Ph.D. in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, or related discipline.
  • Less than 5 years of industrial experience applying scientific and engineering principles to solve complex technical problems.
  • Demonstrated experience in mathematical modeling of physical systems and experimental method development.
  • Strong background in computational modeling, data analysis, and scientific computing.
  • Proficiency with MATLAB, Python, Maple, or similar technical computing environments.

  • Expert knowledge in at least some of the following areas:
    • Transport phenomena
    • Fluid mechanics
    • Polymer mechanics
    • Contact mechanics
    • Fracture mechanics
    • Tribology
    • Surface characterization
    • Materials characterization
    • Comfortable working across theory, simulation, experimentation, and characterization.
    • Strong interpersonal and collaboration skills with multidisciplinary technical teams


Desired Skills:

  • Familiarity with CMP consumables, processes, and polishing mechanisms.
  • Understanding of polyurethane structure-property-performance relationships.

  • Experience with:
    • Finite Element Analysis (FEA/FEM)
    • Computational Fluid Dynamics (CFD)
    • Multiphysics Simulation
    • Model Verification & Validation (V&V)
    • Uncertainty Quantification
    • Sensitivity Analysis
    • Hands-on experience with:
    • ANSYS
    • Abaqus
    • COMSOL
    • High Performance Computing (HPC)

  • Experience evaluating:
    • Model assumptions, governing equations, and constitutive relationships
    • Numerical stability, convergence behavior, and solution robustness
    • Mesh and time-step independence studies
    • Boundary condition selection and sensitivity analyses
    • Model calibration, parameter estimation, and uncertainty quantification
    • Solver performance, computational efficiency, and runtime optimization
    • Verification and validation (V&V) methodologies for predictive engineering models
    • Correlation of simulation predictions with experimental observations and physical behavior

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