Lead Scientist/Engineer - Molecular Modeling Specialist

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We are excited to share that on May 22, 2024, DuPont announced plans to separate(1) into three industry-leading, independent publicly traded companies. This strategic move will create focused businesses with distinct investment profiles. We believe the proposed separations will create opportunities for all three future companies to better serve their customers and unlock long-term value for stakeholders. This process is expected to take 18-24 months from the date of announcement to complete. We are committed to supporting our employees throughout this transition and ensuring a smooth and successful separation process. We look forward to welcoming new talent who are interested in contributing to the continued success and growth of our evolving organization.

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Our purpose is to empower the world with essential innovations to thrive. We work on things that matter! 

Have the Opportunity to chart your own course, challenge yourself, and acquire new capabilities to build a rewarding and fulfilling career. We reward employees with competitive pay and incentives to recognize skills, competencies, and contributions to business results. 

Get to Experience a collaborative environment where teamwork is celebrated with flexibility that enhances balance and an inclusive atmosphere that is welcoming to all!

Get to know our Purpose and make it yours by bringing innovations to market that improve the world, share a commitment to sustainability that makes our planet better and give back to communities in which we work and live.

Lead Scientist/Engineer - Molecular Modeling Specialist

Position Overview: This role focuses on using molecular modeling and machine learning to advance the development of innovative photoresists used in lithography applications. We seek a candidate to drive the optimization of material formulations through computational techniques, facilitating rapid design and testing of new photoresist materials. The candidate will collaborate closely with interdisciplinary teams to utilize data-driven approaches that enhance material performance and reliability.

Key Responsibilities:

• Develop and optimize photoresist formulations using molecular modeling techniques and machine learning algorithms to predict material properties and performance.
• Conduct quantum mechanical calculations and simulations to analyze chemical descriptors relevant to photoresist development.
• Collaborate with data scientists and machine learning engineers to create and refine AI training datasets that improve predictive models for photoresist characteristics.
• Create and maintain internal software tools for multi-target optimization and data post-processing, significantly reducing calibration times and increasing efficiency.
• Train and mentor junior team members on molecular modeling methodologies and machine learning applications in material science.

Qualifications:

• Ph.D. in Chemical Engineering or a related field with a strong focus on molecular modeling and machine learning.
• At least 5 years of relevant experience in photoresist development, molecular simulations, and high-performance computing.
• Expertise in Density Functional Theory (DFT) and its applications in material development.
• Proficient in Python programming and experienced with machine learning frameworks (e.g., scikit-learn, PyMatgen).
• Strong understanding of quantum mechanics, molecular dynamics, and computational chemistry tools.
• Excellent communication and collaboration skills to work effectively in interdisciplinary teams.
• Proven track record of contributing to successful research projects and publications.

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(1)The separation transactions are subject to satisfaction of customary conditions, including final approval by DuPont's Board of Directors, receipt of tax opinion from counsel, the filing and effectiveness of Form 10 registration statements with the U.S. Securities and Exchange Commission, applicable regulatory approvals, and satisfactory completion of financing.  For further discussion of risks, uncertainties and assumptions that could impact the achievement, expected timing and intended benefits of the separation transactions, see DuPont’s announcement.