ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in Fort Mill, SC

Lowe's

Lead AI Engineer - AI Platform

Charlotte, NC · On-site

$100K - $131K/yr

... of advanced machine learning (ML) models, including deep learning (DL) frameworks and large ... physics, economics, data science, information science, or quantitative analytics 5 years of ...

Lowe's

Sr AI Engineer - Physical AI

Charlotte, NC · On-site

$102K - $140K/yr

This role sits at the intersection of robotics, computer vision, machine learning, and data ... physics, economics, data science, information science, or quantitative analytics 3 years of ...

Wells Fargo

Lead Data Science Consultant

Charlotte, NC · Hybrid

... Machine Learning and Statistical Models from idea generation to objective formulation to implementation and deliverables o Masters degree in Computer Science, Mathematics, Statistics, Physics ...

previous page

Showing results 41-60

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in Fort Mill, SC

Physics Informed Machine Learning information

See Fort Mill, SC salary details

$4

$17

$22

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

As of Aug 18, 2026, the average hourly pay for physics informed machine learning in Fort Mill, SC is $17.63, according to ZipRecruiter salary data. Most workers in this role earn between $10.96 and $22.40 per hour, depending on experience, location, and employer.

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 Fort Mill, SC?

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

What job categories do people searching Physics Informed Machine Learning jobs in Fort Mill, SC look for?

The top searched job categories for Physics Informed Machine Learning jobs in Fort Mill, SC are:

What cities near Fort Mill, SC are hiring for Physics Informed Machine Learning jobs?

Cities near Fort Mill, SC with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you

Post-Doctoral Fellow

University of North Carolina at Charlotte

Charlotte, NC • On-site

$48K - $53K/yr

Full-time

Re-posted 5 days ago

The University Of North Carolina At Charlotte rating

6.6

Company rating: 6.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

499th of 618 rated colleges and universities

Job description

Position Information
General Information
Position Number
POST40
Working Title
Post-Doctoral Fellow
Division
Academic Affairs
Department
College of Engineering (Col)
Work Unit
Mechanical Engineering and Engineering Science
Work Location
Duke
Vacancy Open To
All Candidates
Position Designation
Post Doc
Employment Type
Temporary - Full-time
Hours per week
40
Work Schedule
Varies
Pay Rate
$48,000-$53,000
Minimum Experience/Education
A Postdoctoral Fellow (""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop further the research skills acquired in their doctoral programs or to learn new research techniques, in preparation for an academic or research career. In the process of further developing their own research skills, it is expected that Postdoctoral Fellows will also play a significant role in the performance of research at the University and augment the role of graduate faculty in providing research instruction to graduate students. A Postdoctoral Fellow works under the supervision of a regular faculty member, who serves as a mentor to the Fellow, and it is expected that the faculty mentor will impart the realities, and variety, of scientific careers, and will encourage experiences outside the laboratory to broaden postdocs' aspirations. Within the confines of the particular research focus assigned by that faculty member, the Postdoctoral Fellow functions with a considerable degree of independence and has the freedom (and is expected) to publish the results of his or her research or scholarship during the period of appointment. Thus, the role of Postdoctoral Fellows is clearly differentiated from full-time technical employees.
Postdoc appointments are characterized by all the following conditions:
* the appointee was recently (within the last five years) awarded a Ph.D. or equivalent doctorate (e.g., Sc.D., M.D.);
* the appointment is temporary;
* the appointment involves substantially full-time research or scholarship;
* the appointment is viewed as preparatory for a full-time academic and/or research career;
* the appointee works under the supervision of a faculty member; and
* the appointee has the freedom and is expected to publish the results of his or her research or scholarship during the period of appointment.
As an EOE/AA employer and an ADVANCE Institution that strives to create an academic climate in which the dignity of all individuals is respected and maintained, the University of North Carolina at Charlotte encourages applications from all underrepresented groups. Applicants subject to criminal background check.
The candidate chosen for this position will be required to provide an official transcript of their highest earned degree.
The candidate chosen for this position will be subject to a criminal background check.
The appointment length will be for up to 12 months, with the potential for extension based on performance and the availability of funding.
Departmental Preferred Experience, Skills, Training/Education:
Seeking a Postdoctoral Research Fellow to become part of our additive manufacturing (AM)research group at Additive Manufacturing Technology Laboratory (AMTL) within the Department of Mechanical Engineering and Engineering Science at the University of North Carolina at Charlotte.
This is a fantastic opportunity for someone with a strong background in metal/ceramic AM to advance the manufacturing process for near-net-shape parts using powder feedstock methods such as laser powder bed fusion (LPBF) and binder jetting AM. The ideal candidate will have extensive experience in the field and a deep understanding of the mechanical behavior of materials. Experience with LPBF and binder jet machines is crucial for this role.
  1. PhD in Mechanical Engineering, Materials Science, or a related field
  2. Previous experience in material/process development of metal/ceramics
  3. Experience with LPBF and binder jet machines
  4. A proven track record of productive and innovative research, as evidenced by publications in peer-reviewed journals
  5. A solid background in the mechanical behavior of materials
  6. Proficiency in multi-physics FE simulations, topology optimization, and working knowledge of machine learning (ML) algorithms
  7. Demonstrated exceptional problem-solving abilities, a passion for collaborative research, and a commitment to making a tangible real-world impact

Duties and Responsibilities
  1. Perform fundamental theoretical and experimental research on LPBF and binder jetting of metallic/ceramic materials
  2. Plan and execute intricate experiments, and systematically gather as well as analyze the resulting multimodal datasets
  3. Formulate and integrate constitutive models for LPBF and binder jetting AM into FE codes for application in process optimization studies
  4. Utilize ML algorithms and optimization frameworks in conjunction with FE simulations to develop process optimization framework for metal/ceramic AM
  5. Collaborate with fellow researchers and technical staff to discuss simulation, production, and material characterization
  6. Author and publish original research articles in peer-reviewed journals

Other Work/Responsibilities
Necessary Licenses or Certifications
Proposed Hire Date
01/15/2026
Contact Information
Expected Length of Assignment
12 months (1 Year)
Posting Open Date
09/24/2025
Posting Close Date
01/01/2026
Special Notes to Applicants
The candidate chosen for this position will be required to provide an official transcript of their highest earned degree.
The candidate chosen for this position will be subject to a criminal background check.
Submit a cover letter and curriculum vitae and the following:
  • Research statement describing your background and interests (1-2 pages)
  • Provide contact info for 3 references
  • Include a sample publication.

What The University Of North Carolina At Charlotte employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply