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Physics Informed Machine Learning Jobs in Oregon

Natera

OR

You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed ...

Intel

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

Please be informed that Intel is proactively trying to find candidates for this position which is ... machine learning engineering, data science or ML research. * Experiences designing and building ...

Upstart

Applied Scientist

OR · On-site +1

... physics, econometrics, operations research, computer science, or a related quantitative field. * 0-2 years of experience conducting machine learning, statistical modeling, or applied quantitative ...

New

Pwc

AI Engineer

Portland, OR · On-site

$55K - $187K/yr

... machine learning solutions - Conducting complex data analysis to identify patterns and trends for informed decision-making - Collaborating with internal teams to enhance data infrastructure and ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

PRIMARY RESPONSIBILITIES * Hands-on development and write algorithms in machine learning ... Signal processing or physics-based modeling * Graph-based reasoning or causal inference * Full ...

Pwc

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Deloitte

Lead AI and Data Science Engineer II

Portland, OR

$108K - $143K/yr

Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ... informed people and business decisions by translating workforce data into actionable insights ...

Five9

OR

$126K - $166K/yr

Operating at the intersection of advanced machine learning and human-centric design, you will ... Make informed strategic decisions amidst ambiguity. Objectively evaluate product performance ...

Pwc

CTIO AI Engineering Manager

Portland, OR · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

AI Solutions Engineering Delivery Lead

Portland, OR

$108K - $143K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Intel

Yield Development Engineer

Hillsboro, OR · On-site

Extract insights from structured and unstructured data using machine learning, coding techniques ... Expertise in semiconductor physics and advanced device interactions modeling. * Experience ...

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Physics Informed Machine Learning information

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Oregon? For Physics Informed Machine Learning jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Oregon look for? The top searched job categories for Physics Informed Machine Learning jobs in Oregon are:
What cities in Oregon are hiring for Physics Informed Machine Learning jobs? Cities in Oregon with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Oregon as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Machine Learning Scientist, Multimodal AI

Natera

OR

Other

Re-posted 8 days ago

Natera rating

7.6

Company rating: 7.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

60th of 120 rated laboratories

Job description

POSITION SUMMARY:

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.

PRIMARY RESPONSIBILITIES:

  • Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features
  • Develop multimodal AI architectures that integrate H&E whole-slide imaging data with molecular and clinical data sources
  • Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS)
  • Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning
  • Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools
  • Analyze model outputs to generate reproducible biological and clinical insights
  • Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders

QUALIFICATIONS:

  • PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI
  • Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics
  • Hands-on expertise with PyTorch and strong production-level programming skills in Python
  • Practical application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning
  • Experience managing datasets and training workflows within distributed or cloud computing environments (AWS)
  • Proven ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows
  • Experience adapting pre-trained foundation models for downstream biomedical applications

PREFERRED QUALIFICATIONS:

  • Experience integrating imaging, molecular, and clinical data within unified multimodal machine learning frameworks
  • Technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays
  • Hands-on experience with digital pathology software and whole-slide imaging analysis
  • Exposure to survival modeling, longitudinal prediction, or time-to-event modeling
  • Experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data
  • Domain knowledge in oncology, biomarker discovery, or clinical precision medicine
  • Track record of peer-reviewed publications in machine learning or computational biology conferences and journals (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering)

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