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Physics Simulation Python Jobs in Knoxville, TN (NOW HIRING)

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Physics Simulation Python information

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$10.5K

$64.5K

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How much do physics simulation python jobs pay per year?

As of Jun 27, 2026, the average yearly pay for physics simulation python in Knoxville, TN is $64,517.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $75,900.00 per year, depending on experience, location, and employer.

What is the difference between Physics Simulation Python vs Mechanical Engineer?

AspectPhysics Simulation PythonMechanical Engineer
Required CredentialsProgramming skills, knowledge of physics, often a degree in physics or computer scienceMechanical engineering degree, professional licensure in some regions
Work EnvironmentSoftware development, research labs, simulation environmentsDesign offices, manufacturing plants, R&D departments
Industry UsageSimulation software development, research, academiaProduct design, manufacturing, systems optimization

Physics Simulation Python focuses on developing and implementing physics-based simulations using Python programming, often in research or software development contexts. Mechanical Engineers apply engineering principles to design, analyze, and manufacture mechanical systems. While both roles require a strong understanding of physics, Physics Simulation Python emphasizes coding and simulation, whereas Mechanical Engineering involves practical design and application in physical systems.

What are the key skills and qualifications needed to thrive as a Physics Simulation Python Developer, and why are they important?

To excel as a Physics Simulation Python Developer, you need a strong background in physics, mathematics, and proficiency in Python programming, often supported by a degree in physics, engineering, or computer science. Familiarity with simulation libraries (such as NumPy, SciPy, PyBullet, or SimPy), version control systems like Git, and experience with visualization tools are commonly required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills in this role. These skills enable the development of accurate, efficient simulations and foster productive teamwork in research or engineering projects.

What are some common challenges faced by professionals working in Physics Simulation with Python, and how can they be addressed?

Professionals in Physics Simulation with Python often encounter challenges such as optimizing simulation performance, ensuring numerical accuracy, and integrating complex libraries (e.g., NumPy, SciPy, PyBullet) into larger workflows. Addressing these issues typically involves using efficient coding practices, leveraging vectorized operations, and validating results with analytical solutions or experimental data. Collaboration with domain experts and regular code reviews can also help maintain code reliability and project scalability. Staying updated with the latest simulation frameworks and actively participating in open-source communities are excellent ways to overcome technical hurdles.

What is a Physics Simulation Python developer?

A Physics Simulation Python developer is a professional who uses the Python programming language to design, implement, and analyze simulations that model physical systems and phenomena. These simulations can range from simple particle motion to complex fluid dynamics or electromagnetic fields, and are widely used in research, engineering, gaming, and education. The developer typically utilizes scientific libraries such as NumPy, SciPy, and PyBullet, and may also work with visualization tools to present simulation results. Their work helps in understanding real-world physics problems, testing hypotheses, or creating realistic interactive environments.
What are popular job titles related to Physics Simulation Python jobs in Knoxville, TN? For Physics Simulation Python jobs in Knoxville, TN, the most frequently searched job titles are:
What job categories do people searching Physics Simulation Python jobs in Knoxville, TN look for? The top searched job categories for Physics Simulation Python jobs in Knoxville, TN are:
Infographic showing various Physics Simulation Python job openings in Knoxville, TN as of June 2026, with employment types broken down into 54% Full Time, 25% Part Time, and 21% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $64,517 per year, or $31 per hour.
Postdoctoral Research Associate - AI Models for Power Grid System

Postdoctoral Research Associate - AI Models for Power Grid System

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

3rd of 103 rated laboratories


Job description

Requisition Id 16687
Overview:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows.
Major Duties/Responsibilities:
  • Participate in the design, implementation, and deployment of scalable AI/DL models for power grid systems, including surrogate models and foundation-model workflows for OPF and related grid simulation tasks.
  • Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and institutional clusters.
  • Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines.
  • Author peer reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences.
  • Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, electrical engineers, domain scientists, and applied mathematicians conducting basic and applied AI/DL research in support of the Laboratory's missions.

Basic Qualifications:
  • A PhD in computer science or an AI-related field completed within the last 5 years.
  • Demonstrated expertise in scalable deep learning, including distributed training and/or large-scale inference using modern AI frameworks such as PyTorch.
  • Demonstrated experience with high-performance computing systems, including multi-node workflows on CPU and/or GPU clusters.
  • Demonstrated expertise in scalable data management for AI/ML workflows, including efficient data preprocessing, storage, streaming, and I/O for large scientific datasets.
  • Demonstrated experience writing SLURM and PBS job submission scripts for HPC clusters, including batch workflows, job arrays, environment setup, and restart logic.
  • Demonstrated expertise with the Linux operating system, bash scripting, Git, Python, and reproducible software environments.
  • Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep learning algorithms.
  • Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes.
  • Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills.

Preferred Qualifications:
  • Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured scientific or engineering data.
  • Background in electrical engineering, power systems, grid modeling, or power system optimization.
  • Experience with optimal power flow and grid simulation solvers or toolchains, such as MATPOWER, PSS/E, PowerModels, or related open-source or commercial packages.
  • Experience working in a multi-disciplinary research environment that follows modern software quality standards, including version control, unit testing, documentation, and continuous integration.
  • Motivated self-starter with the ability to work independently, participate creatively in collaborative teams, function well in a fast-paced research environment, and adapt to evolving project needs.

Special Requirements:
Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.
Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application.
Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.
Instructions to upload documents to your candidate profile:
  • Login to your account via jobs.ornl.gov
  • View Profile
  • Under the My Documents section, select Add a Document

Technical questions:
Massimiliano Lupo Pasini (lupopasinim@ornl.gov), Alex Plotkowski (plotkowskiaj@ornl.gov)
About ORNL:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.
Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.
This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.
If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.
ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.

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