The role focuses on scientific machine learning, automated AI/ML optimization, and high-performance ... modeling, physics-informed neural networks, or uncertainty quantification for scientific ...
The role focuses on scientific machine learning, automated AI/ML optimization, and high-performance ... modeling, physics-informed neural networks, or uncertainty quantification for scientific ...
This position centers on scientific machine learning, automated AI/ML optimization, and high ... Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
This position centers on scientific machine learning, automated AI/ML optimization, and high ... Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
This position centers on scientific machine learning, automated AI/ML optimization, and high ... Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
This position centers on scientific machine learning, automated AI/ML optimization, and high ... Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
Physics-informed and hybrid AI (AI + simulation + experimental data fusion) * AI-HPC co-design ... Machine learning / AI * Scientific computing / HPC * Data-intensive science * Strong track record ...
Physics-informed and hybrid AI (AI + simulation + experimental data fusion) * AI-HPC co-design ... Machine learning / AI * Scientific computing / HPC * Data-intensive science * Strong track record ...
Physics-informed and hybrid AI (AI + simulation + experimental data fusion) * AI-HPC co-design ... Machine learning / AI * Scientific computing / HPC * Data-intensive science * Strong track record ...
Physics-informed and hybrid AI (AI + simulation + experimental data fusion) * AI-HPC co-design ... Machine learning / AI * Scientific computing / HPC * Data-intensive science * Strong track record ...
... data analytics and machine learning (ML), and data-model integration, leveraging the U.S ... Design and implement physics-informed and physics-ML hybrid approaches that integrate domain ...
... data analytics and machine learning (ML), and data-model integration, leveraging the U.S ... Design and implement physics-informed and physics-ML hybrid approaches that integrate domain ...
... data analytics and machine learning (ML), and data-model integration, leveraging the U.S ... Design and implement physics-informed and physics-ML hybrid approaches that integrate domain ...
... data analytics and machine learning (ML), and data-model integration, leveraging the U.S ... Design and implement physics-informed and physics-ML hybrid approaches that integrate domain ...
Data Science Consultant
Nashville, TN · On-site
Required : • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. • At least 2+ years of industry ...
Data Science Consultant
Nashville, TN · On-site
Required : • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. • At least 2+ years of industry ...
Artificial Intelligence & Machine Learning Engineer (Senior Consultant)
Nashville, TN · On-site
$118.30K - $156K/yr
Artificial Intelligence & Machine Learning Engineer (Senior Consultant) At Fearless, this ... informed. * Shape client engagement and intelligence-gathering efforts by actively cultivating ...
Artificial Intelligence & Machine Learning Engineer (Senior Consultant)
Nashville, TN · On-site
$118.30K - $156K/yr
Artificial Intelligence & Machine Learning Engineer (Senior Consultant) At Fearless, this ... informed. * Shape client engagement and intelligence-gathering efforts by actively cultivating ...
Machine Learning Scientist - AI Trainer
Nashville, TN · On-site +1
$40/hr
Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...
Machine Learning Scientist - AI Trainer
Nashville, TN · On-site +1
$40/hr
Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...
Machine Learning Scientist - AI Trainer
Nashville, TN · On-site +1
$40/hr
Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...
Machine Learning Scientist - AI Trainer
Nashville, TN · On-site +1
$40/hr
Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...
Postdoctoral Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling
Oak Ridge, TN · On-site
... machine learning, contributing to interdisciplinary research and collaboration efforts across ... with physics-based simulations to accelerate discovery and improve predictive fidelity • ...
Postdoctoral Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling
Oak Ridge, TN · On-site
... machine learning, contributing to interdisciplinary research and collaboration efforts across ... with physics-based simulations to accelerate discovery and improve predictive fidelity • ...
... physics, electrical engineering, or mechanical engineering who are interested in experimental ... quantum machine learning. Applicants with expertise in quantum optics and quantum information ...
... physics, electrical engineering, or mechanical engineering who are interested in experimental ... quantum machine learning. Applicants with expertise in quantum optics and quantum information ...
Post-Doctoral Research Associate: Department of Physics and Astronomy - UTK
Knoxville, TN · On-site
$67K - $70K/yr
... physics, electrical engineering, or mechanical engineering who are interested in experimental ... quantum machine learning. Applicants with expertise in quantum optics and quantum information ...
Post-Doctoral Research Associate: Department of Physics and Astronomy - UTK
Knoxville, TN · On-site
$67K - $70K/yr
... physics, electrical engineering, or mechanical engineering who are interested in experimental ... quantum machine learning. Applicants with expertise in quantum optics and quantum information ...
A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. * At least 2+ years of industry experience outside ...
A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. * At least 2+ years of industry experience outside ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
... students informed about their progress through the prompt grading of papers and other work ... Knowledge of current teaching and learning strategies to facilitate student-centered learning ...
The successful candidate will develop and apply advanced machine learning techniques--including ... Knowledge of scientific domains such as engineering systems, physics-based modeling, or quantum ...
The successful candidate will develop and apply advanced machine learning techniques--including ... Knowledge of scientific domains such as engineering systems, physics-based modeling, or quantum ...
The successful candidate will develop and apply advanced machine learning techniques-including ... Knowledge of scientific domains such as engineering systems, physics-based modeling, or quantum ...
The successful candidate will develop and apply advanced machine learning techniques-including ... Knowledge of scientific domains such as engineering systems, physics-based modeling, or quantum ...
Physics Informed Machine Learning information
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 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.
More about Physics Informed Machine Learning jobs
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:
- Remote Data Scientist Intern
- Generative Ai Writer
- Senior Applied Scientist Machine Learning
- Part Time Machine Learning Scientist
- Scientific Machine Learning
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- Machine Learning Researcher
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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:
Postdoctoral Research Associate - Data Scientist
Oak Ridge National LaboratoryOak Ridge, TN • On-site
Full-time
Posted 7 days ago
Oak Ridge National Laboratory rating
9.3
Based on 15 frontline employees who took The Breakroom Quiz
4th of 103 rated laboratories
Job description
Job Summary:
Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher to join the Workflow Systems Group to advance the use of AI in scientific discovery. The role focuses on scientific machine learning, automated AI/ML optimization, and high-performance computing, contributing to research efforts supported by the U.S. Department of Energy Office of Science.
Responsibilities:
• Conduct research and development in scalable AI/ML methods for scientific computing and high-performance computing environments.
• Develop and evaluate optimization techniques for machine learning workflows, including approaches for model tuning, automated model design, and adaptive search strategies.
• Contribute to research in uncertainty quantification, surrogate modeling, and other methods that improve the robustness and reliability of AI-driven scientific applications.
• Design and implement distributed and parallel approaches that efficiently leverage large-scale computing resources, including heterogeneous CPU/GPU systems, along with the possibility of working with Quantum computing.
• Collaborate with interdisciplinary research teams to integrate AI/ML capabilities into scientific simulation, data analysis, and computational workflows.
• Contribute to the development and maintenance of open-source software, including testing, documentation, and user support activities.
• Work closely with researchers and domain scientists to communicate results, define research directions, and support collaborative projects.
• Publish research findings in peer-reviewed journals and present work at scientific workshops and conferences.
• Design and implement scalable AI/ML optimization algorithms for hyperparameter optimization and neural architecture search, targeting scientific machine learning models running on leadership-class HPC systems.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.
Qualifications:
Required:
• A PhD in Computer Science, Applied Mathematics, Computational Science, Data Science, or a related discipline completed within the last three years.
• An excellent record of productive and creative research as demonstrated by publications in top peer-reviewed journals and conferences.
• Demonstrated experience with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and hyperparameter optimization or AutoML techniques.
• Proficiency in Python and familiarity with software engineering best practices (version control, testing, documentation).
• Experience with HPC environments and parallel/distributed computing.
• Strong problem-solving and communication skills, with the ability to work collaboratively in a team setting.
Preferred:
• Experience with multi-fidelity optimization, neural architecture search, or large-scale AutoML systems.
• Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty quantification for scientific applications.
• Prior exposure to DOE workflows, national laboratory environments, or large-scale simulation codes.
• Experience contributing to open-source scientific software projects.
Company:
Oak Ridge National Laboratory holds a range of R&D assignments, from fundamental nuclear physics to applied R&D on advanced energy systems. Founded in 1943, the company is headquartered in Oak Ridge, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher to join the Workflow Systems Group to advance the use of AI in scientific discovery. The role focuses on scientific machine learning, automated AI/ML optimization, and high-performance computing, contributing to research efforts supported by the U.S. Department of Energy Office of Science.
Responsibilities:
• Conduct research and development in scalable AI/ML methods for scientific computing and high-performance computing environments.
• Develop and evaluate optimization techniques for machine learning workflows, including approaches for model tuning, automated model design, and adaptive search strategies.
• Contribute to research in uncertainty quantification, surrogate modeling, and other methods that improve the robustness and reliability of AI-driven scientific applications.
• Design and implement distributed and parallel approaches that efficiently leverage large-scale computing resources, including heterogeneous CPU/GPU systems, along with the possibility of working with Quantum computing.
• Collaborate with interdisciplinary research teams to integrate AI/ML capabilities into scientific simulation, data analysis, and computational workflows.
• Contribute to the development and maintenance of open-source software, including testing, documentation, and user support activities.
• Work closely with researchers and domain scientists to communicate results, define research directions, and support collaborative projects.
• Publish research findings in peer-reviewed journals and present work at scientific workshops and conferences.
• Design and implement scalable AI/ML optimization algorithms for hyperparameter optimization and neural architecture search, targeting scientific machine learning models running on leadership-class HPC systems.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.
Qualifications:
Required:
• A PhD in Computer Science, Applied Mathematics, Computational Science, Data Science, or a related discipline completed within the last three years.
• An excellent record of productive and creative research as demonstrated by publications in top peer-reviewed journals and conferences.
• Demonstrated experience with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and hyperparameter optimization or AutoML techniques.
• Proficiency in Python and familiarity with software engineering best practices (version control, testing, documentation).
• Experience with HPC environments and parallel/distributed computing.
• Strong problem-solving and communication skills, with the ability to work collaboratively in a team setting.
Preferred:
• Experience with multi-fidelity optimization, neural architecture search, or large-scale AutoML systems.
• Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty quantification for scientific applications.
• Prior exposure to DOE workflows, national laboratory environments, or large-scale simulation codes.
• Experience contributing to open-source scientific software projects.
Company:
Oak Ridge National Laboratory holds a range of R&D assignments, from fundamental nuclear physics to applied R&D on advanced energy systems. Founded in 1943, the company is headquartered in Oak Ridge, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
What Oak Ridge National Laboratory employees say
Pay
Hours and flexibility
Workplace
Get the full story on Breakroom
About Oak Ridge National Laboratory
Sourced by ZipRecruiter
Industry
Scientific research and development services
Company size
5,001 - 10,000 Employees
Headquarters location
Oak Ridge, TN, US
Year founded
1943