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Physics Informed Machine Learning Jobs in Huntingdon Valley, PA

Develop mechanistic, statistical, hybrid, and/or machine learning models that translate complex ... physics, bioinformatics, data science, applied mathematics, or a related discipline, with at least ...

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Develop mechanistic, statistical, hybrid, and/or machine learning models that translate complex ... physics, bioinformatics, data science, applied mathematics, or a related discipline, with at least ...

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Physics Informed Machine Learning information

See Huntingdon Valley, PA salary details

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

As of Aug 15, 2026, the average hourly pay for physics informed machine learning in Huntingdon Valley, PA is $19.68, according to ZipRecruiter salary data. Most workers in this role earn between $12.26 and $25.00 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?

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 job categories do people searching Physics Informed Machine Learning jobs in Huntingdon Valley, PA look for?

The top searched job categories for Physics Informed Machine Learning jobs in Huntingdon Valley, PA are:

What cities near Huntingdon Valley, PA are hiring for Physics Informed Machine Learning jobs?

Cities near Huntingdon Valley, PA with the most Physics Informed Machine Learning job openings:

Research Scientist - Applied Artificial Intelligence in Chemistry

Universal Display Corporation

Trenton, NJ โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 days ago


Job description

At Universal Display Corporation (Nasdaq: OLED) (UDC), we’re changing the way people see the world.
If you’re reading this on a smartphone, there’s a good chance UDC’s materials are producing the light and color shining from your screen right now. UDC’s OLED ingredients are key parts of stunning, energy-efficient displays used in everything from smartwatches to phones, tablets, laptops, monitors, TVs and automobiles. Virtually every OLED consumer electronics product around the world uses UDC’s phosphorescent OLED materials and technologies.
UDC is a publicly traded company and pioneer in the OLED industry. When you join our global team, you are embarking on a journey at the forefront of display technology and organic electronics that impacts the daily lives of people around the world. From engineers to chemists, Ph.D. scientists, technicians, lawyers and more, our UDC team is continuously advancing our field. With a focus on energy efficiency, UDC’s team is contributing to making a better, more sustainable planet. Please visit us at www.oled.com .
Job Summary:
Universal Display Corporation is seeking a Research Scientist to develop and deploy practical AI/ML capabilities that accelerate molecular discovery and materials research. This role will apply modern machine learning, generative molecular design, agentic AI workflows, and scientific software development across chemistry-focused R&D programs. The ideal candidate has hands-on experience applying AI/ML to chemistry problems, can work across data curation, model development, and workflow deployment, and is motivated by close collaboration with computational scientists, synthetic chemists, and device engineers to advance new materials from concept toward experimental validation.


Key Responsibilities:

  • Design, implement, and evaluate machine learning models for chemistry and materials applications, including molecular property prediction, representation learning, and structure-property relationship modeling.

  • Develop and apply generative molecular design methods to propose candidate compounds and materials with target properties relevant to OLED and organic electronics research.

  • Curate, analyze, and improve scientific datasets used for AI/ML model training, validation, benchmarking, and deployment in practical R&D workflows.

  • Build and maintain applied AI workflows, including agentic AI systems, tool-harnessed LLM workflows, and scientific application components that support chemistry-focused decision making.

  • Collaborate closely with ML scientists, computational chemists, synthetic chemists, and device engineers to interpret model outputs, guide experiments, and identify promising molecular leads for synthesis and testing.

  • Contribute to applied AI/ML infrastructure that enables reproducible model development, deployment, monitoring, and integration with computational chemistry and experimental workflows.

Required Qualifications:

  • PhD in Chemistry, Chemical Engineering, Materials Science, Physics, Computer Science, or a related field, with demonstrated experience applying AI/ML methods to chemistry or molecular materials problems.

  • Proven experience developing machine learning models for chemistry, including molecular property prediction and hands-on generative molecular design.

  • Strong working knowledge of modern AI/ML approaches relevant to molecular systems, including molecular featurization, transformer-based models, and deep learning workflows.

  • Proficiency in Python for scientific programming and data analysis, including hands-on experience with RDKit, PyTorch, and related scientific Python libraries.

  • Experience developing agentic AI workflows, LLM tool harnesses, or AI-enabled scientific applications that connect models, tools, data, and user workflows.

  • Excellent communication and collaboration skills, with the ability to work effectively with ML scientists, computational chemists, synthetic chemists, and device engineers.

Preferred Qualifications:

  • Advanced research experience applying AI/ML to molecular discovery, computational chemistry, materials science, or related applied R&D problems.

  • Background in molecular chemistry, organic electronics, OLED materials, or organic semiconductors.

  • Experience with graph neural networks, PyTorch Geometric or related frameworks, recurrent neural networks, sequence models, or other molecular deep learning architectures.

  • Experience with machine-learned interatomic potentials, molecular simulation workflows, or AI/ML methods that support atomistic modeling.

  • Experience with exploratory data analysis, scientific data curation, model benchmarking, or deployment of ML-enabled scientific workflows.

Current Benefits at UDC:

  • Competitive base salary and annual bonus program

  • Medical/Prescription Drug coverage, Dental, and Vision for employees and family

  • Option between Flexible Spending account (FSAs) or Health Savings Account (HSA)

  • Group Term Life insurance, short term disability, and long-term disability benefits for employees

  • Employee Stock Purchase Plan (ESPP)

  • 401(k) company contribution

  • Ewing Worldwide Headquarters (HQ) cafeteria provides breakfast and lunch to employees at no cost to them

  • Annual charitable matching gift

  • Generous Paid Time Off

Annual compensation range: $115k-140k

At Universal Display Corporation, base pay is one part of our total compensation package. Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the annual salary range only, and does not include bonus, equity or sales incentives, if applicable.