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Physics Informed Machine Learning Jobs in Norfolk, VA

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 ...

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 ...

Senior Data Scientist

Hampton, VA · On-site

$99K - $225K/yr

... machine learning or other approaches. You'll use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help Air Force leaders make informed ...

... machine learning or other approaches. You'll use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help Air Force leaders make informed ...

As our data scientist, you'll lead advanced analytic efforts and drive data-informed decision ... Design and develop machine learning models, including recommendation engines and automated scoring ...

As our data scientist, you'll lead advanced analytic efforts and drive data-informed decision ... scalable machine learning (ML) solutions, and develop AI-driven tools to automate analytical ...

... physics for high-speed aerospace systems. This role supports system design and optimization by ... Apply advanced data science techniques with machine learning to build surrogate models of CFD ...

Data Scientist

Langley, VA · On-site

$99K - $225K/yr

... machine learning, and semantic technologies in mission-critical environments. We deliver cutting ... Our work drives operational excellence and enables informed decision-making across complex domains ...

Data Scientist

Hampton, VA · On-site

$99K - $225K/yr

... machine learning, and semantic technologies in mission-critical environments. We deliver cutting ... Our work drives operational excellence and enables informed decision-making across complex domains ...

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Physics Informed Machine Learning information

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

As of Jul 4, 2026, the average hourly pay for physics informed machine learning in Norfolk, VA is $19.41, according to ZipRecruiter salary data. Most workers in this role earn between $12.12 and $24.66 per hour, depending on experience, location, and employer.

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 job?

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 Norfolk, VA? For Physics Informed Machine Learning jobs in Norfolk, VA, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Norfolk, VA look for? The top searched job categories for Physics Informed Machine Learning jobs in Norfolk, VA are:
What cities near Norfolk, VA are hiring for Physics Informed Machine Learning jobs? Cities near Norfolk, VA with the most Physics Informed Machine Learning job openings:
Faculty in Applications of Physics, Data Science and/or Engineering to Particle Accelerators (Tenure

Faculty in Applications of Physics, Data Science and/or Engineering to Particle Accelerators (Tenure

Old Dominion University

Norfolk, VA • On-site

Full-time

Posted 10 days ago


Old Dominion University rating

7.5

Company rating: 7.5 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

268th of 544 rated colleges and universities


Job description

Posting Details
Posting Details
Job Title
Faculty in Applications of Physics, Data Science and/or Engineering to Particle Accelerators (Tenured, F1117A
Department
AI CLUSTER HIRE INITIATIVE
Position Number
F1117A
Job Description
The Department of Physics and the Center for Accelerator Science at Old Dominion University invite applicants for a tenured Associate or Full Professor position (depending on experience) in Accelerator Science as part of a multi-position hiring initiative for Applications of Physics , Data Science, and/or Engineering to Particle Accelerators.
The appointee will maintain a vibrant, externally funded interdisciplinary research program in accelerator science using artificial intelligence (AI)/machine learning (ML), engineering, physics and/or related scientific approaches to study topics such as accelerator design and development, advanced performance optimization and analysis of accelerators, large-scale simulations of accelerator performance, and control optimization of accelerators using advanced AI/ML techniques. Collaboration with other faculty in Physics, Engineering, and the School of Data Science at ODU as well as accelerator scientists at the nearby Thomas Jefferson National Accelerator Facility (Jefferson Lab) will be encouraged.
Other Responsibilities:
  • Teach undergraduate and graduate courses, including for the Virginia Innovative Traineeship in Accelerators (VITA) program and the US Particle Accelerator School (USPAS).
  • Advise graduate students.
  • Provide service to their department and the University.

Position Type
FullTime
Type of Recruitment
General Public
Type of Recruitment
General Public
Minimum required education and/or special licenses, registrations, trainings, or certifications
A Ph.D. or equivalent in Physics, Computer Science, Mathematics, Engineering, or a closely related field is required.
Minimum required level and type of experience, knowledge, skills, and abilities
Candidates must have expertise in the field of accelerator science, broadly defined, and experience indicative of the ability or interest to teach and/or mentor at the undergraduate and graduate levels.
Candidates must also have the following:
  1. Academic records that merit a tenured appointment in the Department of Physics or El at ODU.
  2. A successful record in research and externally funded grants.
  3. Demonstrated ability to interact and communicate clearly with internal and external constituencies.

Preferred Qualifications
  • Postdoctoral experience in Accelerator Science or a related field
  • A strong publication record and/or experience with grant-funded research.
  • Research relating to understanding and improving the CEBAF accelerator at Jefferson Lab, designing and building the Electron-Ion Collider (EIC), exploring future nuclear physics accelerators, improving the performance of light sources, developing new concepts for accelerators for nuclear and high-energy physics, nuclear medicine and other applications, or visualization and control of accelerators.

Conditions of Employment
Location
Norfolk, VA
Job Open Date
07/25/2026
Application Review Date
Open Until Filled
Yes
Application Instructions
Interested candidates must complete the online application at https://jobs.odu.edu/postings/23811, including the following:
  1. A cover letter describing your relevant qualifications and indicating the rank you would like to be considered for.
  2. A curriculum vitae.
  3. A statement of teaching philosophy.
  4. A statement of research interests.
  5. Unofficial graduate transcripts.
  6. Contact information for 3 professional references. At the appropriate time in the Search process, these individuals will be contacted by the Search Committee.

Applications should be submitted full consideration. The positions will remain open until filled.
Questions about these positions should be directed to Dr. Sebastian Kuhn (skuhn@odu.edu), Chair of the Applications of Physics, Data Science, and/or Engineering to Particle Accelerators" Cluster Hire.
Telework Friendly
No
Reasonable Accommodation Request
If you are an individual with a disability and require reasonable accommodation, please contact the Division of Talent Management and Culture at (757)683-3141.
Pay Transparency Nondiscrimination Provision
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or © consistent with contractor's legal duty to furnish information.
About the College
https://www.odu.edu/scihttps://www.odu.edu/engineeringhttps://www.odu.edu/interdisciplinary-schools
About the Department
About the Center for Accelerator Science: Hampton Roads is the host of the Thomas Jefferson National Accelerator Facility (Jefferson Lab), one of the premier accelerator facilities in the world and the pioneer of superconducting radiofrequency technology. ODU has capitalized on the proximity of this National Lab through its longstanding collaboration with Jefferson Lab in Nuclear Physics (since the 1990's). In 2008, ODU, with the support of Jefferson Lab, created the Center for Accelerator Science (CAS), to expand this collaboration. As a result, ODU is one of the few academic institutions in the country and the world where the next-generation accelerator scientists and engineers can be trained to provide the needed workforce for the design, construction, and operation of particle accelerators. Since its creation in 2008, CAS has received more than $16M in external funding and has graduated over 25 Ph.D. students. Many of those students now have leadership positions in DOE laboratories. CAS faculty, staff, and students are key participants and have a leading role in several large-scale international accelerator projects.
For more information, visit: https://www.odu.edu/physics, https://www.odu.edu/center-for-accelerator-science

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