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Physics Informed Machine Learning Jobs in Suffolk, VA

Ironclad Defense Works

Data Scientist / AI Engineer

Norfolk, VA · On-site

$115 - $130/hr

  • Medical

  • Dental

  • Retirement

  • PTO

... physics, computer science, software engineering, or a closely related discipline. * At least four years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer ...

Williammary

Research Scientist

Gloucester Point, VA · On-site

$65K/yr

... informed decision-making on resource management issues at all levels of government, including ... Experience integrating AI or machine learning approaches into environmental modeling * Experience ...

Photon

GenAI Solution Architect - VA

Norfolk, VA

$61 - $80.25/hr

They must possess knowledge of Python, and machine learning frameworks. Responsibilities Develop ... Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or ...

Photon

GenAI Solution Architect - VA

Norfolk, VA · On-site

$61 - $80.25/hr

They must possess knowledge of Python, and machine learning frameworks. Responsibilities Develop ... Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or ...

CACI International, Inc.

Data Scientist

Norfolk, VA · On-site

  • Medical

  • Retirement

  • PTO

Apply advanced methods including machine learning, statistical modeling, and artificial ... Physics, Computer Science, or a relevant technical field. Masters Degree preferred (In lieu of the ...

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Physics Informed Machine Learning information

See Suffolk, VA salary details

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How much do physics informed machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for physics informed machine learning in Suffolk, VA is $19.09, according to ZipRecruiter salary data. Most workers in this role earn between $11.88 and $24.23 per hour, depending on experience, location, and employer.

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 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 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 popular job titles related to Physics Informed Machine Learning jobs in Suffolk, VA?

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What job categories do people searching Physics Informed Machine Learning jobs in Suffolk, VA look for?

The top searched job categories for Physics Informed Machine Learning jobs in Suffolk, VA are:

What cities near Suffolk, VA are hiring for Physics Informed Machine Learning jobs?

Cities near Suffolk, VA 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 Suffolk, VA as of June 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $39,699 per year, or $19.1 per hour.

Senior Consultant - Computational Aerothermodynamics & Machine Learning

Analytical Mechanics Associates, Inc.

Hampton, VA • On-site

$81.28 - $95.05/hr

Other

Medical, Dental, Vision, Retirement

Re-posted 9 days ago

Job description

Responsibilities
  • Technical Advisory: Provide expert-level consultation on computational aerothermodynamics methodologies, physics-based modeling, and simulation strategies.
  • Machine Learning Integration: Advise on the application and integration of machine learning algorithms (e.g., surrogate modeling, physics-informed neural networks, data‑driven turbulence modeling) to enhance traditional CFD and aerothermodynamic workflows.
  • Design & Architecture Review: Evaluate and provide feedback on the architecture of high‑performance physical models and numerical methods.
  • Strategic Roadmapping: Assist engineering teams in identifying emerging trends and state-of-the-art techniques in M&S and computational physics to maintain a competitive technical edge.
  • Mentorship & Collaboration: Serve as a sounding board for senior engineers and developers, helping to troubleshoot complex physical and algorithmic challenges.
Qualifications
  • Required Qualifications
    • Education: Ph.D. in Aerospace Engineering, Mechanical Engineering, Physics, or a strictly related computational discipline.
    • Experience: Minimum of 5 years of active, post‑Ph.D.-level professional experience focused on computational aerothermodynamics, M&S, and ML.
    • Domain Expertise: Deep foundational knowledge of hypersonic and supersonic flows, high‑temperature gas dynamics, and advanced CFD.
    • Machine Learning Proficiency: Proven track record of applying ML, deep learning, or advanced statistical modeling to complex fluid dynamics or thermodynamic problems.
    • Communication: Exceptional ability to distill complex theoretical concepts into actionable engineering guidance.
  • Preferred Qualifications
    • Familiarity with modern, high‑performance software architecture, particularly robust C++ libraries for CFD codes.
    • Experience with heterogeneous computing environments, including GPU acceleration and parallel programming models (OpenMP, CUDA, Kokkos).
    • Deep knowledge of physics of high‑enthalpy flows, including thermal radiation, chemical kinetics, and transport processes.
    • History of peer‑reviewed publications in relevant aerospace, physics, or computational science journals.
  • U.S. Citizenship or Permanent Residence required.
Job Details

Part‑time advisory consultant; 20 hours per month; hourly rate \$59–\$69, commensurate with experience and education.

Company Overview

Analytical Mechanics Associates (AMA) is a small business headquartered in Hampton, VA, with operations in Greenbelt, MD; Huntsville, AL; Dallas & Houston, TX; Denver, CO; Mountain View, CA; and Edwards Air Force Base, CA. AMA has over 60 years of experience specializing in aerospace engineering, science, analytics, information technology, and visualization solutions.

Benefits

Competitive salaries and benefits including paid personal and federally recognized holiday leave, salary deferral 401(k) matching, tuition reimbursement, short/long‑term disability plans, and medical, dental, and vision insurance.

Equal Opportunity Employer

AMA is an Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.

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