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Computational Modeling Jobs in Oregon (NOW HIRING)

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 ...

These will be the models that detect cancer in the minimal residual disease (MRD) setting and help ... Translate between wet-lab experimental design and computational analysis, navigating ambiguity as ...

Senior Software Engineer - NVIDIA Warp

OR · On-site +1

$122K - $161K/yr

Substantial work building, optimizing, and supporting computational software used in research or production, involving numerical methods, model validation, or scientific data pipelines. Ways to stand ...

Ability to explain modeling techniques for physical systems, approximation methods, and stability analysis while preparing students for engineering, physics, finance, and computational science ...

Showing results 21-40

Computational Modeling information

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$43

$58

$78

How much do computational modeling jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for computational modeling in Oregon is $58.07, according to ZipRecruiter salary data. Most workers in this role earn between $49.57 and $77.79 per hour, depending on experience, location, and employer.

What is computational modeling?

A Computational Modeling job involves developing and using mathematical models, simulations, and algorithms to analyze complex systems across various fields, such as engineering, physics, biology, and finance. Professionals in this role apply computational techniques to study real-world phenomena, predict outcomes, and optimize processes. They often work with programming languages, statistical methods, and high-performance computing to create accurate and efficient models.

What does a computational modeler do?

A typical day for a computational modeling professional often involves developing and refining mathematical or computer-based models, running simulations, and analyzing large datasets to draw meaningful conclusions. You’ll collaborate closely with domain experts, engineers, and researchers to ensure models accurately reflect real-world processes. The role may also involve presenting findings to stakeholders, troubleshooting code or software issues, and keeping up with new modeling techniques and industry advancements. This dynamic environment requires balancing independent problem-solving with teamwork and communication.

What are the key skills and qualifications needed to thrive in computational modeling?

To thrive in computational modeling, a strong background in mathematics, computer science, and domain-specific knowledge (such as engineering, physics, or biology) is essential, often supported by at least a bachelor's or master's degree in a related field. Familiarity with programming languages like Python, MATLAB, or R, as well as experience with simulation software and data analysis tools, is typically required. Strong problem-solving, analytical thinking, and effective communication skills set outstanding candidates apart. These abilities enable professionals to build accurate models, collaborate successfully with interdisciplinary teams, and translate complex results into actionable insights.

What are the most commonly searched types of Computational Modeling jobs in Oregon?

The most popular types of Computational Modeling jobs in Oregon are:

What are popular job titles related to Computational Modeling jobs in Oregon?

For Computational Modeling jobs in Oregon, the most frequently searched job titles are:

What cities in Oregon are hiring for Computational Modeling jobs?

Cities in Oregon with the most Computational Modeling job openings:

Infographic showing various Computational Modeling job openings in Oregon as of September 2026, with employment types broken down into 1% Internship, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $120,794 per year, or $58.1 per hour.

Machine Learning Scientist, Multimodal AI

OR • On-site, Remote

Natera
Biotechnology Research and Development • 1 - 5K employees

Full-time

Re-posted 13 days ago


Natera rating

7.8

Company rating: 7.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

56th of 121 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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