ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in North Carolina

Cree

Manager of Research Science

Durham, NC

Use your previous expertise in AI/ML techniques for computer vision, physics informed ML, and ... Materials Science, chemical engineering, physics, electrical Engineering, Machine Learning or ...

Siemens

Principal Data Scientist

Raleigh, NC · On-site

$122K - $210K/yr

Operationalize machine learning systems: Work with ML engineering and product teams to deploy ... Experience with digital twins, simulation, or physics-informed modeling * Experience building or ...

Wells Fargo

Lead Machine Learning Engineer

Charlotte, NC · Hybrid

$100K - $131K/yr

... informed decision-making at scale. In this role, you will leverage Google Cloud Platform (GCP ... Design data architectures for training, validation and monitoring of predictive machine learning as ...

Corning

Machine Vision Engineer

Hickory, NC

$88K - $121K/yr

... Optics, Physics, or a related field. Experience: 2+ years of combined engineering, manufacturing ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Corning

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

... Optics, Physics, or a related field. Experience: 2+ years of combined engineering, manufacturing ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Corning

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

... Optics, Physics, or a related field. Experience: 2+ years of combined engineering, manufacturing ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Deloitte

AI Engineer - SFL Scientific

Charlotte, NC · On-site

... Physics, etc.) or equivalent experience • 2+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment • 2+ ...

Deloitte

AI Solutions Architect

Charlotte, NC

$61.50 - $81/hr

Leading sales, solution design, and delivery for artificial intelligence, machine learning ... or Physics, or equivalent experience * 8+ years of experience in product sales, software ...

Deloitte

AI Solutions Architect

Raleigh, NC

$61.25 - $80.75/hr

Leading sales, solution design, and delivery for artificial intelligence, machine learning ... or Physics, or equivalent experience * 8+ years of experience in product sales, software ...

Deloitte

Senior AI Engineer - SFL Scientific

Charlotte, NC · On-site

$102K - $140K/yr

... Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment • 4+ ...

Deloitte

Senior AI Engineer - SFL Scientific

Raleigh, NC · On-site

$101K - $139K/yr

... Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment • 4+ ...

next page

Showing results 1-20

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in North Carolina

Physics Informed Machine Learning information

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 North Carolina? For Physics Informed Machine Learning jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in North Carolina look for? The top searched job categories for Physics Informed Machine Learning jobs in North Carolina are:
What cities in North Carolina are hiring for Physics Informed Machine Learning jobs? Cities in North Carolina with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Postdoctoral Appointee: Physics-Informed AI for Microelectronics Materials

Postdoctoral Appointee: Physics-Informed AI for Microelectronics Materials

Argonne National Laboratory

Lumberton, NC • On-site

$70K - $117K/yr

Full-time

Posted 6 days ago

Job description

The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials. Working within an interdisciplinary team, you will develop frameworks that connect atomistic features, mesoscale dynamics, and device-level performance. The effort will integrate heterogeneous data from simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales.

Key Responsibilities

  • Design, implement, and validate physics-informed AI/ML models for microelectronics materials

  • Curate, manage, and integrate heterogeneous datasets from experiments and simulations

  • Collaborate closely with experimental teams to benchmark and refine computational models

  • Disseminate research through publications, presentations, and open-source contribution

Position Requirements

  • Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field

  • Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) applied to scientific problems

  • Strong background in managing multimodal datasets

  • Proven experience collaborating with experimental teams to validate computational models

  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Preferred Qualifications

  • Deep understanding of AI/ML concepts, including transformers, latent-space representations, generative models, and reinforcement learning

  • Experience with high-performance computing, physics-based simulations, and multimodal data workflows

  • Demonstrated ability to train and deploy AI/ML models using simulated and experimental data

  • Familiarity with agentic LLM-based approaches and related technologies (e.g., RAG, MCP, A2A)

  • Interest in interfacial phenomena and defect dynamics in materials across scales

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full timeThe expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

Apply