Universal Display Corporation is seeking to develop machine learning models that predict chemical properties and design new compounds and materials to improve OLED technology
Requirements
- PhD in Chemistry, Physics, or a related field (e.g., Chemical Engineering, Materials Science)
- Proven experience applying machine learning to chemical problems, including developing both property prediction (inferential) models and generative models (demonstrated through peer-reviewed publications or successful practical applications)
- Familiarity with a broad range of machine learning approaches relevant to chemistry, such as tree-based models, fingerprint-based similarity methods, multi-layer perceptrons (MLPs), and graph neural network models
- Proficiency in Python for scientific programming and data analysis, including experience with relevant libraries/frameworks (e.g., PyTorch, RDKit, PyG, etc.)
- Postdoctoral research experience (2+ years) or equivalent advanced research experience applying AI/ML in chemistry
- Background in organic electronics or related fields (e.g., OLED materials, organic semiconductors) is highly valued
- Experience with machine learned interatomic potentials (MLIP) including training and implementation is a plus
- Experience developing user interfaces or graphical tools for scientific software applications (GUI design skills)
Responsibilities
- Design and implement state-of-the-art machine learning models (e.g., tree-based algorithms, fingerprint-based methods, multi-layer perceptrons, and graph neural networks) to predict chemical and material properties with unparalleled accuracy
- Develop and apply generative AI techniques to propose new molecules or materials with desired target properties that push past the limitations of today’s OLEDs
- Continuously refine and validate predictive models to improve accuracy and reliability ensuring they meet the highest standards for molecular property prediction and compound design
- Work closely with team members in the computational group to seamlessly integrate AI approaches with traditional chemical research methods such as laboratory experiments, molecular simulations, and quantum chemistry calculations
- Partner with other R&D scientists to interpret model predictions, guide experiment design, and identify promising leads for new compounds or materials
Other
- Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment
- Competitive base salary and annual bonus program
- Medical/Prescription Drug coverage, Dental, and Vision for employees and family
- Transit, Health and Dependent Care Flexible Spending Accounts (FSAs)
- Group Term Life insurance, short term disability, and long term disability benefits for employees
