Research Scientist - Applied Artificial Intelligence in Chemistry

Job Description

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  .

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.