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Causal Inference Machine Learning Postdoctoral Jobs in Hillsboro, OR

AI Engineer, Sr

Newberg, OR

$109K - $150K/yr

Build and maintain machine learning models and AI services used in production environments * Design ... Experience optimizing costs for LLMs and agentic systems in cloud environments, including inference ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Build and maintain machine learning models and AI services used in production environments * Design ... Experience optimizing costs for LLMs and agentic systems in cloud environments, including inference ...

Showing results 41-48

Causal Inference Machine Learning Postdoctoral information

See Hillsboro, OR salary details

$38.7K

$59.1K

$66.4K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Aug 14, 2026, the average yearly pay for causal inference machine learning postdoctoral in Hillsboro, OR is $59,053.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,300.00 and $61,500.00 per year, depending on experience, location, and employer.

What is a causal inference machine learning postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Hillsboro, OR look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Hillsboro, OR are:

Modeling Engineer 5 (Thermal, CFD, AI/ML)

Lam Research Corporation

Tualatin, OR • On-site

Full-time

Re-posted 13 days ago


Lam Research rating

8.2

Company rating: 8.2 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

130th of 489 rated machine equipment manufacturers


Job description

The group you'll be a part of
In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.
The impact you'll make
We move atoms that move the world.
At Lam Research, we create equipment that allows chipmakers to build device features more than 1,000 times smaller than a grain of sand. This tiny scale has a huge impact. Virtually every leading-edge chip inside the electronic products you use every day (TVs, smartphones, laptops, cars-even medical devices) has been made using our equipment.
As one of the world's most trusted suppliers in the semiconductor equipment industry, we're transforming technology. Our equipment places atoms so precisely that nearly every chip today is made using our innovations.
To build a prosperous career, start with an atom.
Should you choose to walk the path historically driven by Moore's law, your primary job function will involve cutting edge R&D activities in the Semiconductor Equipment Industry. If solving challenges no one has faced before or attempted are of interest to you, then Lam Research is the company for you.
What you'll do
  • Developing physics-based models for Thermal/CFD/Chemistry applications for components in semiconductor capital equipment industry. Experience in commercial software like ANSYS Fluent, Star CCM+, or COMSOL, etc., is highly desirable.
  • Strong ability in closed-form solutions and analytical methods development and understanding fundamentals in fluid mechanics.
  • Utilizing DOE, Optimization, and statistical methods and data driven modeling to correlate Simulation data to experimental data.
  • Predict, measure, and analyze the experimental data for uncertainty Quantification & propagation, sensitivity analysis, statistical inference for model calibration, decision making under uncertainty.
  • Multi-scale modeling from nano, meso to macro levels
  • Provide design improvements of in-service tools based upon quantitative field measured failure data and less quantitative quality metrics as measured by Lam Research.
  • Provide written reports and oral presentation of results to design teams and management.
  • Work directly with mechanical, electrical, process and software engineers to define design requirements, goals and objectives of design, CIP, testing and simulation plans.
  • Strong written and oral communication. Self-starter to start own initiatives and projects for continuous improvement in capabilities and design.
  • Put your running shoes on: In this job you'll work in a highly dynamic and rapidly changing environment within a team of interdisciplinary experts driving to solutions to the most challenging business needs.

Who we're looking for
  • PhD in Mechanical Engineering or closely related field with strong emphasis in Computational Fluid Dynamics, Heat transfer, Chemistry, or related fields with >6 years of experience in a related industry, e.g., semiconductor, gas turbine, aerospace, automotive, etc.
  • Ability to work with a team to drive product development and design decisions. Propose design concepts and own decisions.
  • Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software. Building and maintaining codes of AI/ML models with either simulation or test data. Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc.) and deep learning.
  • Coding ability to supplement commercial software for specific applications as needs arise.
  • Knowledge of chemistry, semiconductor metrology methods, and hardware designs in a vacuum environment is also a plus.
  • General understanding of uncertainty quantification, Bayesian optimization and probabilistic machine learning is required.

Preferred qualifications
  • Ability to effectively communicate and build relationships to interact, inform, influence, and communicate with key stakeholders at all levels across the company.
  • Strong critical thinking skills demonstrated through problem-solving, attention to detail and innovation.
  • Strong analytical skills demonstrated through First Principles Thinking, statistical Analysis and Physics-based Insights

Our commitment
We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.
Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.
Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
IND123 #LI-NB1 #LI-Onsite
Our Perks and Benefits
At Lam, our people make amazing things possible. That's why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.

What Lam Research employees say

Pay

Benefits

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About Lam Research

Sourced by ZipRecruiter

Lam Research designs and builds products for semiconductor manufacturing, including equipment for thin film deposition, plasma etch, photoresist strip, and wafer cleaning processes.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Fremont, CA, US

Year founded

1980

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