Post-Doctoral Scientist - Synthetic Molecule Design and Development (SMDD) - FDE

at  Lilly

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

BASIC QUALIFICATIONS

• Ph.D. in Computational Chemistry
• Demonstrated use of Python ecosystem for development/deployment of machine learning models applicable to modeling organic chemistry.

ADDITIONAL SKILLS/PREFERENCES

If you are described with these skills, you could be a great fit for the role:

• Self-directed and highly motivated individual who wants to learn new techniques while continually pursuing research and publication goals.
• Excellent communicator (oral and written) with presentation experience, along with a strong publication record.
• Ability to explain complex computational techniques and workflows to scientists not trained as computational chemists.
• Proficient in data analysis and reporting
• Familiarity with the basics of physical organic chemistry, including both molecule structural and reaction mechanism principles.
• Demonstrated experience and application of computational chemistry tools such as Gaussian, Molecular Operating Environment (MOE) or other quantum mechanical method software.
• Demonstrated experience with application of chemoinformatics tools (i.e. RDkit) for developing machine learning models.
• Experienced with designing, executing and interpreting DFT calculations for understanding of organic chemical reaction mechanisms.
• Experience developing/optimizing computational pipelines incorporating quantum mechanical models and machine learning algorithms in python (i.e. SciKit Learn).

• Self-directed and highly motivated individual who wants to learn new techniques while continually pursuing research and publication goals.
• Excellent communicator (oral and written) with presentation experience, along with a strong publication record.
• Ability to explain complex computational techniques and workflows to scientists not trained as computational chemists.
• Proficient in data analysis and reporting
• Familiarity with the basics of physical organic chemistry, including both molecule structural and reaction mechanism principles.
• Demonstrated experience and application of computational chemistry tools such as Gaussian, Molecular Operating Environment (MOE) or other quantum mechanical method software.
• Demonstrated experience with application of chemoinformatics tools (i.e. RDkit) for developing machine learning models.
• Experienced with designing, executing and interpreting DFT calculations for understanding of organic chemical reaction mechanisms.
• Experience developing/optimizing computational pipelines incorporating quantum mechanical models and machine learning algorithms in python (i.e. SciKit Learn)