... machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational ...
... machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational ...
... physics-informed machine learning, data-driven surrogate modeling, reinforcement learning, or agentic AI. • Proficiency in C++, Python, MATLAB, or similar for algorithm development and software ...
... physics-informed machine learning, data-driven surrogate modeling, reinforcement learning, or agentic AI. • Proficiency in C++, Python, MATLAB, or similar for algorithm development and software ...
Postdoctoral Research Associate
Boston, MA · On-site
$60.32K - $85.19K/yr
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 ...
Postdoctoral Research Associate
Boston, MA · On-site
$60.32K - $85.19K/yr
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 ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL ...
Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL ...
Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning ...
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
Quick apply
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
Quantum Calibrations Intern, Quantum Computing Services
Boston, MA · On-site
$16.25 - $21.75/hr
... physics-informed models of device behavior, and develop predictive tools for real-time qubit state ... Experience applying machine learning (Gaussian processes, time-series models, or neural networks ...
Quantum Calibrations Intern, Quantum Computing Services
Boston, MA · On-site
$16.25 - $21.75/hr
... physics-informed models of device behavior, and develop predictive tools for real-time qubit state ... Experience applying machine learning (Gaussian processes, time-series models, or neural networks ...
Quantum Calibrations Intern, Quantum Computing Services
$16.25 - $21.75/hr
... physics-informed models of device behavior, and develop predictive tools for real-time qubit state ... Experience applying machine learning (Gaussian processes, time-series models, or neural networks ...
Quantum Calibrations Intern, Quantum Computing Services
$16.25 - $21.75/hr
... physics-informed models of device behavior, and develop predictive tools for real-time qubit state ... Experience applying machine learning (Gaussian processes, time-series models, or neural networks ...
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
D. students with experience in some of the following: audio signal processing, microphone array processing, source separation, physics informed machine learning, outlier detection, and unsupervised ...
Machine Learning Engineer
Cambridge, MA · On-site
We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or ...
Machine Learning Engineer
Cambridge, MA · On-site
We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or ...
Physics Informed Machine Learning information
See Boston, MA salary details
$5.75 - $7.74
0% of jobs
$7.74 - $9.73
0% of jobs
$9.73 - $11.73
0% of jobs
$11.73 - $13.72
24% of jobs
$13.82 is the 25th percentile. Wages below this are outliers.
$13.72 - $15.72
16% of jobs
$15.72 - $17.71
0% of jobs
$17.71 - $19.71
0% of jobs
$19.71 - $21.70
0% of jobs
$21.70 - $23.69
0% of jobs
The median wage is $24.17 / hr.
$23.69 - $25.69
40% of jobs
$25.69 - $27.68
19% of jobs
$5
$21
$27
How much do physics informed machine learning jobs pay per hour?
As of May 28, 2026, the average hourly pay for physics informed machine learning in Boston, MA is $21.80, according to ZipRecruiter salary data. Most workers in this role earn between $13.56 and $27.69 per hour, depending on experience, location, and employer.
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 Boston, MA? For Physics Informed Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
- Data Scientist Intern
- Machine Learning Researcher
- Remote Assay Development Scientist
- Internship Fraud Data Scientist
- Remote Data Scientist Intern
- Part Time Machine Learning Research Scientist
- Freelance Machine Learning Data Annotation
- Scientific Machine Learning
- Machine Learning Scientist
- Data Science For Social Good
What job categories do people searching Physics Informed Machine Learning jobs in Boston, MA look for? The top searched job categories for Physics Informed Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Physics Informed Machine Learning jobs? Cities near Boston, MA with the most Physics Informed Machine Learning job openings:
Full-time
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McKinsey & Company rating
8.5
Based on 22 frontline employees who took The Breakroom Quiz
14th of 57 rated business consultants
Job description
Job Summary:
McKinsey & Company is a global management consulting firm that focuses on driving lasting impact and building long-term capabilities with clients. They are seeking a Specialist in Robotics and Physical AI who will apply expertise in physical sciences and machine learning to solve complex engineering challenges for industrial clients, leading technical workstreams and developing innovative solutions.
Responsibilities:
• Apply deep expertise in physical sciences, computational engineering, machine learning, and physics-based modeling to help leading industrial clients tackle their most complex engineering challenges.
• Lead technical workstreams on client engagements, building multi-physics simulation frameworks and digital twins, developing surrogate and machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational insights into strategic recommendations and solutions that deliver measurable impact for clients.
Qualifications:
Required:
• Advanced graduate degree (M.S. or Ph.D.) in computational mechanics, materials science, mechanical/aerospace/nuclear engineering, computational physics, or a closely related engineering or physical science field required; significant industry or national laboratory experience in applied simulation or scientific machine learning may apply
• Demonstrated ability to develop high-quality engineering or scientific code (e.g., in Python, C++)
• Demonstrated fluency with statistical sampling, machine learning, and data science techniques
• Excellent organizational capabilities, including the ability to initiate tasks independently and see them through to completion
• Proficient in rational decision making based on data, facts, and logical reasoning
• Ability to create work product-focused materials / outputs, which may include PowerPoint decks, Excel models, articles, or other written deliverables
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
• Ability to work or attend meetings outside of traditional business hours or take on projects with limited or no notice at times
• Ability to travel to and work in varying environments that may be challenging and/or not accessible (e.g., manufacturing facilities, etc.)
• Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels
Preferred:
• Simulation experience, Pytorch, ML/AI/Data Science a plus
Company:
McKinsey & Company is a global management consulting firm and trusted advisor by businesses, governments, and institutions. Founded in 1926, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.
McKinsey & Company is a global management consulting firm that focuses on driving lasting impact and building long-term capabilities with clients. They are seeking a Specialist in Robotics and Physical AI who will apply expertise in physical sciences and machine learning to solve complex engineering challenges for industrial clients, leading technical workstreams and developing innovative solutions.
Responsibilities:
• Apply deep expertise in physical sciences, computational engineering, machine learning, and physics-based modeling to help leading industrial clients tackle their most complex engineering challenges.
• Lead technical workstreams on client engagements, building multi-physics simulation frameworks and digital twins, developing surrogate and machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational insights into strategic recommendations and solutions that deliver measurable impact for clients.
Qualifications:
Required:
• Advanced graduate degree (M.S. or Ph.D.) in computational mechanics, materials science, mechanical/aerospace/nuclear engineering, computational physics, or a closely related engineering or physical science field required; significant industry or national laboratory experience in applied simulation or scientific machine learning may apply
• Demonstrated ability to develop high-quality engineering or scientific code (e.g., in Python, C++)
• Demonstrated fluency with statistical sampling, machine learning, and data science techniques
• Excellent organizational capabilities, including the ability to initiate tasks independently and see them through to completion
• Proficient in rational decision making based on data, facts, and logical reasoning
• Ability to create work product-focused materials / outputs, which may include PowerPoint decks, Excel models, articles, or other written deliverables
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
• Ability to work or attend meetings outside of traditional business hours or take on projects with limited or no notice at times
• Ability to travel to and work in varying environments that may be challenging and/or not accessible (e.g., manufacturing facilities, etc.)
• Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels
Preferred:
• Simulation experience, Pytorch, ML/AI/Data Science a plus
Company:
McKinsey & Company is a global management consulting firm and trusted advisor by businesses, governments, and institutions. Founded in 1926, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.
What McKinsey & Company employees say
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