Qualifications

• Bachelor's degree in Computer Science, Data Science, Computational Chemistry, Cheminformatics, or related field with relevant ML modeling experience.
• Domain knowledge in chemistry, preferably polymer chemistry.
• Ability to develop molecular and materials representations and evaluate predictive models.
• Experience in applied statistics and uncertainty quantification, including model calibration.
• Strong Python skills and familiarity with mainstream Python-based ML tools.
• Experience using AI-assisted coding tools and knowledge of emerging ML methods.
• Strong communication and collaboration skills for interfacing with cross-functional teams.

Responsibilities

• Lead ML model development for predictions and optimizations in chemistry and formulation.
• Collaborate with R&D and manufacturing to translate business goals into modeling tasks.
• Curate and analyze chemical and experimental data to assess modeling limits.
• Develop input representations for various data types relevant to modeling.
• Select, train, and evaluate diverse modeling approaches including neural networks and Gaussian processes.
• Quantify model performance and define validity domains for practical application.
• Utilize transfer learning across multiple data sources to enhance model utility.
• Explore and implement cutting-edge ML techniques to improve modeling capabilities.
• Communicate technical methods and results effectively to varied audiences.

Benefits

• Supportive environment for interdisciplinary collaboration.
• Opportunity to work on innovative ML methods in a chemistry context.
• Access to cutting-edge tools and technologies for model development.