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Physics Informed Machine Learning Jobs in Denver, CO

Anduril Industries

Senior Software Engineer

Broomfield, CO · On-site

$123K - $162K/yr

... physics, engineering, or other technical field (advanced degree strongly preferred) • C/C ... optimization • Machine learning: supervised and unsupervised learning, clustering, and ...

Neara

Forward Deployed Engineer - USA (Denver)

Denver, CO · On-site

$130K - $200K/yr

We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges ...

Pwc

Pharma Technology Consultant Manager

Denver, CO · On-site

$99K - $232K/yr

... enabling informed decision-making and driving business growth within our Data and Analytics ... Responsibilities - Leading the design and development of AI and Machine Learning solutions for ...

New

Fanatics Betting & Gaming

Data Scientist III

Denver, CO

$117K - $167K/yr

... Physics, Statistics, Engineering, or Computer Science, Economics. * Strong SQL proficiency and strong proficiency in Python, with experience building and validating machine learning models. * Strong ...

Anduril Industries

Senior Software Engineer

Broomfield, CO

$123K - $162K/yr

Bachelor's degree in mathematics, physics, engineering, or other technical field (advanced degree ... Machine learning: supervised and unsupervised learning, clustering, and classification; * Applied ...

Pwc

CTIO AI Engineering Manager

Denver, CO

$73K - $244K/yr

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

As of Jun 27, 2026, the average hourly pay for physics informed machine learning in Denver, CO is $20.65, according to ZipRecruiter salary data. Most workers in this role earn between $12.88 and $26.25 per hour, depending on experience, location, and employer.

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 Denver, CO? For Physics Informed Machine Learning jobs in Denver, CO, the most frequently searched job titles are:
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What cities near Denver, CO are hiring for Physics Informed Machine Learning jobs? Cities near Denver, CO with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you

NIST PREP Postdoctoral Research Associate for Analysis of Real-World Mid-Band Aggregate Cellular Net

Southeastern Universities Research Association

Boulder, CO • On-site

$82K - $110K/yr

Full-time

Posted 7 days ago

Job description

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title: Analysis of Real-World Mid-Band Aggregate Cellular Network Emissions
The work will entail:Conduct applied research implementing and developing data analysis methods for large, high-quality datasets of mid-band (3 GHz - 4 GHz) radio frequency (RF) spectrum measurements of deployed 4G and 5G cellular networks. New data analysis methods and insights resulting from this position will help improve models for aggregate RF emissions, interference assessments, and deployments of cellular networks. Position will require in-person work at NIST in Boulder, Colorado.
Key responsibilities will include but are not limited to:
  • Implement advanced data analysis and data visualization methods in python.
  • Work with NIST research scientists to extract meaningful insights from data.
  • Research into novel data analysis methods.
  • Prepare software and data for publication.
  • Prepare manuscripts suitable for peer-reviewed publication.
  • Present findings at academic conferences and stakeholder meetings.

Qualifications
  • U.S. Citizenship
  • PhD in Electrical Engineering, Computer Science, Data Science, Statistics, Applied Mathematics, Physics, or closely related field received within the last 5 years.
  • Excellent programming skills in python, including familiarity with the Pandas and NumPy libraries.
  • Ability to work effectively in a collaborative research environment.
  • Ability to generate independent research ideas.
  • Strong oral and written communication skills.
  • Preferred: Experience with application of advanced data analysis or machine learning methods to large datasets.
  • Preferred: Strong background in statistics.
  • Preferred: Strong background in signal processing.
  • Preferred: Strong background in machine learning.
  • Preferred: Familiarity with fundamentals of wireless communication systems.
  • Preferred: Basic understanding of electromagnetic propagation and radio frequency engineering.
  • Preferred: Track record of successful peer-reviewed publications.

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
PREP0003772

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