Job Description
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Company Overview
An AI and physical sciences company developing advanced models and simulation technologies to accelerate breakthroughs across materials, energy, and other scientific fields. The company combines artificial intelligence, physical science expertise, and computational modeling to address complex problems in areas such as advanced manufacturing and process optimization.
Responsibilities
- Own simulation workflows end-to-end for customer engagements, from model setup and calibration through optimization and interpretation of results.
- Run, debug, and modify physics-based simulations of complex physical processes across domains such as microfluidics, charge transport, and structural deformation.
- Work directly on-site with customer engineering teams to understand process constraints and translate simulation results into practical process improvements.
- Develop tools, skills, and agents that reliably support end-to-end LLM-based simulation workflows, including experimental validation, parameter fitting, and recipe optimization.
- Build and extend simulation tooling in Python for job submission, parameter sweeps, output parsing, and system integration.
- Collaborate with modeling and machine learning teams to build and calibrate physics-based simulations and translate customer process knowledge into computational models.
- Drive recipe optimization through direct feedback loops with production environments.
- Share domain insights with research and product teams to help shape future platform capabilities.
- Travel to and spend extended periods on-site in Taiwan as required for customer engagements.
Qualifications
- Strong foundation in numerical simulation of continuum systems, including areas such as fluid dynamics, heat transfer, structural mechanics, electromagnetics, or related fields.
- Experience gained through graduate research, industry experience, or a combination of both.
- Hands-on experience solving partial differential equations numerically, including mesh generation, solver tuning, and debugging numerical instabilities.
- Strong Python skills for scripting and scientific computing, including experience with NumPy, SciPy, or similar tools.
- Ability to approach simulations as tools for solving real-world process and engineering problems.
- Strong communication skills and comfort working directly with customer engineering teams.
- Willingness to spend extended periods working on-site in Taiwan.
- Self-starter mindset with the ability to take technical problems from definition through deployed results with limited supervision.
Additional Qualifications
- Experience with computational fluid dynamics (CFD) and tools such as OpenFOAM, ANSYS Fluent, Star-CCM+, or custom solvers.
- Graduate-level research experience developing simulation software in areas such as mechanical engineering, chemical engineering, weather modeling, astrophysics, or materials processing.
- Familiarity with semiconductor manufacturing processes.
- Experience with physics-informed machine learning, surrogate modeling, or neural operators for accelerating simulations.
- Experience integrating simulation tools into larger software platforms or automated optimization pipelines.
- Mandarin proficiency for on-site collaboration in Taiwan.
- Laboratory or experimental experience and an understanding of how simulation connects with physical data.
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