Physics Informed Machine Learning Scientist

ASML
San Diego
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: phdSkills: ["Communication","Teamwork","Problem-solving","Leadership","Interpersonal"]

Join ASML's Virtual Source team to develop physics-informed ML pipelines and master models for integrated lithography source architectures. You will build data infrastructures, integrate physics-based models, and run experiments on test benches to guide design decisions and de-risk future configurations, combining data science, physics, and software to enable system-level optimization of EUV sources.

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FursaFursa
ASML
ASML
2 months ago

Physics Informed Machine Learning Scientist

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Last checked: 14 days agoStatus: Live

Job Summary

Join ASML's Virtual Source team to develop physics-informed ML pipelines and master models for integrated lithography source architectures. You will build data infrastructures, integrate physics-based models, and run experiments on test benches to guide design decisions and de-risk future configurations, combining data science, physics, and software to enable system-level optimization of EUV sources.
Location: San Diego
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Establish scalable data management framework spanning legacy and new datasets from test benches and source prototypes, ensuring data quality, accessibility, and structured readiness for seamless integration into ML workflows.
  • •Develop physics-informed machine learning models and scientific simulations to enable system-level tradeoff analysis and drive the definition and optimization of lithography source technology configurations.
  • •Adapt and integrate existing physics-based models into a master virtual model, and establish the necessary infrastructure for deployment and maintenance.
  • •Propose experimental anchoring studies, analyze test results, reduce model uncertainty through correlation building, and extract actionable knowledge from submodule- to full-system-level analysis.
  • •Provide input to technology roadmaps, identify de-risking activities and key scientific learning objectives, and contribute to experimental design to establish design guidelines, performance requirements, and procedures for product teams.

Pay and Benefits

Perks:Health Insurance401kRemote Work

Key Requirements

  • •Ph.D. with a minimum of 3+ years of experience or a Master’s degree with at least 6+ years of experience in an analytical field such as mathematics, physics, or engineering, with extensive experience in physics-informed machine learning and model integration into scalable master models.
  • •Experience solving complex, open-ended modeling problems using optimization and deep learning methodologies, with strong expertise in data management and building scalable data and training pipelines for end-to-end model development and training.
  • •Strong software development skills in Python, with experience in deep learning frameworks (e.g. PyTorch or JAX); proficiency in C/C++, and Matlab is a plus.
  • •Experience with database tools, automation frameworks, and experimental tracking platforms (e.g. MLflow) for managing end to end ML lifecycle.
  • •Experience working in cloud and development environments such as Azure Kubernetes Service (AKS), Google Distributed Cloud Edge (GDCE), Apache Spark, Azure Databricks, and related technologies is a plus.
Experience:3+ yearsPhdMachine learningData managementPythonPytorchJaxC++MatlabMlflowAKSSparkDatabricks
Education:PhD / Doctorate
Skills:CommunicationTeamworkProblem-solvingLeadershipInterpersonal
Tech Stack:PythonPyTorchJAXC/C++MatlabMLflowAzure Kubernetes Service (AKS)Google Distributed Cloud EdgeApache SparkAzure Databricks

Company Brief

ASML
Designs and manufactures advanced photolithography systems for the semiconductor industry, enabling production of integrated circuits at leading-edge process nodes for global chipmakers.
Industry: Industrial Machinery
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Veldhoven, Netherlands
Founded: 1984
Glassdoor
Glassdoor: 4.1
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