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Physics Informed Machine Learning Jobs in Methuen, MA

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Lead Research Scientist - Machine Learning

Woburn, MA · On-site

$174K - $220K/yr

... physics, and data science. We use our expertise and creativity to take innovative ideas from ... Experience adapting novel machine learning approaches (e.g., from academic literature) to new data ...

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Physics Informed Machine Learning information

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$26

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 Methuen, MA is $20.98, according to ZipRecruiter salary data. Most workers in this role earn between $13.08 and $26.63 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 cities near Methuen, MA are hiring for Physics Informed Machine Learning jobs? Cities near Methuen, MA with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you

Postdoctoral Research Associate

Northeastern University

Boston, MA • On-site

$60K - $85K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago

Job description

About the Opportunity
AI-Driven Ultrasound and Intelligent Sensing:
We are seeking a postdoctoral researcher to work on quantitative ultrasound methods, focusing on the application of model-based machine learning techniques to raw ultrasound data. The project involves developing novel algorithms that integrate physics, engineering, and AI to extract meaningful and clinically relevant information directly from raw signals. The work spans algorithm development, advances in model-based AI, and translation to real-world clinical applications, offering an opportunity to contribute to next-generation imaging and diagnostic technologies.
QUALIFICATIONS:
  • Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer Science, Industrial Engineering, or a closely related field (obtained by start date).
  • Demonstrated research experience with quantitative ultrasound methods.
  • Strong background in model-based or physics-informed machine learning, with experience developing algorithms that integrate physics models, engineering principles, and AI techniques.
  • Ability to design, implement, and validate novel algorithms for applied or translational research, ideally with relevance to real-world or clinical imaging applications.
  • Proven research and academic writing experience, including the preparation of high-quality scholarly articles for peer-reviewed journals and conferences.
  • Experienced in mentoring and supervising students on research projects, with demonstrated leadership skills in guiding collaborative work.
  • Excellent communication abilities, including fluent spoken English and strong presentation skills, enabling effective dissemination of research outcomes and active engagement in international academic discussions.

Position Type
Research
Additional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Compensation Grade/Pay Type:
108S
Expected Hiring Range:
$60,315.00 - $85,192.50
With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.

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