ASML

3 weeks ago

Physics Informed Machine Learning Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours 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: 4.1

Website LinkedIn

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ASML

3 weeks ago

Physics Informed Machine Learning Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

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: 4.1

Website LinkedIn