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Physics Informed Machine Learning Jobs in Tennessee

EPB

Quantum Software Engineer Fellow

Chattanooga, TN · On-site

Graduate degree in Computer Science, Engineering, Mathematics, Physics, Quantum Information Science ... Machine learning * Python programming language CERTIFICATIONS & OTHER REQUIREMENTS * US citizenship ...

EPB

Quantum Software Engineer Fellow

Chattanooga, TN

Graduate degree in Computer Science, Engineering, Mathematics, Physics, Quantum Information Science ... Machine learning * Python programming language CERTIFICATIONS & OTHER REQUIREMENTS * US citizenship ...

Deloitte

Lead AI and Data Science Engineer II

Nashville, TN · On-site

$99K - $130K/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 ...

Deloitte

Lead AI and Data Science Engineer II

Memphis, TN · On-site

$99K - $131K/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 ...

Deloitte

Lead AI and Data Science Engineer II

Hermitage, TN · On-site

$89K - $118K/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 ...

Type One Energy

Real-Time Engineer

Knoxville, TN · On-site

  • Retirement

Machine-learning inference * Translating mathematical models into executable real-time code What ... physics and high-field superconducting magnets to develop its optimized stellarator fusion energy ...

Pwc

CTIO AI Engineering Manager

Nashville, TN · On-site

$73K - $244K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

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Physics Informed Machine Learning information

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 Tennessee?

For Physics Informed Machine Learning jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Tennessee look for?

The top searched job categories for Physics Informed Machine Learning jobs in Tennessee are:

What cities in Tennessee are hiring for Physics Informed Machine Learning jobs?

Cities in Tennessee 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 Tennessee as of August 2026, with employment types broken down into 6% Internship, 47% Full Time, 41% Part Time, and 6% Contract. Highlights an 100% In-person job distribution.

Teaching Faculty (Electrical Engineering) - School of Engineering and Physics

Southern Adventist University

College Dale, TN • On-site

Full-time

Re-posted 22 days ago

Southern Adventist University rating

8.1

Company rating: 8.1 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

162nd of 618 rated colleges and universities

Job description

Location: School of Engineering and Physics
Hours: Full-time, Salary
To Begin: Fall 2026
Job Summary: The School of Engineering and Physics is seeking a full-time teaching faculty member in the area of electrical engineering. The ideal candidate will be proficient in developing and teaching undergraduate engineering courses, including both lecture and laboratory components. Candidate may teach both physics and support engineering, and the selected engineering courses. In addition, the successful candidate will be committed to mentoring advisees, nurturing student learning both in and out of the classroom, and discipling students in Jesus Christ.
Duties:
  • Develop and teach general and specialized undergraduate engineering courses within the faculty member's areas of qualification.
  • Appropriately integrate Christian faith and biblical principles as reflected in Seventh-day Adventist beliefs in course content and by personal interactions with students and colleagues.
  • Maintain engineering laboratories, develop safety protocols and a training program for equipment use, and support students' use of laboratory equipment for course and capstone projects.
  • Advise and mentor students in the areas of academic, spiritual, and career development.
  • Sponsor student clubs, tours/trips, senior capstone projects, and special projects.
  • Nurture a culture of collaboration within the School of Engineering and Physics and across the university through meaningful service on departmental and university committees.
  • Practice professional and scholarly engagement.
  • Other duties as assigned.

Special Requirements: Must have an expressed commitment to Jesus Christ and the teachings and mission of the Seventh-day Adventist Church, be an SDA church member in good and regular standing, and desire to serve.
Qualifications: Master's degree in electrical engineering or related area required. Doctorate preferred. Prior higher education teaching experience and/or relevant industry experience preferred. Be able to write and speak English fluently.
Typical Physical Demands: Requires sitting, standing, bending and reaching. May require lifting up to 30 pounds. Requires manual dexterity sufficient to operate standard office machines such as computers, calculators, telephone and other office equipment.
Working Conditions: Essential tasks are performed under normal office/school conditions with little or no noticeable discomfort. Work area is well lighted and ventilated.

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