Senior Scientist (AI-Driven Drug Discovery)

BioSpace; North Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Paid time off

401(k) plan

Long-term incentive programs

Job summary

AbbVie is seeking a scientifically skilled professional to advance AI-enabled drug discovery in our small molecule portfolio. You will collaborate with medicinal chemists, structural biologists, and chemoinformatics experts to identify, develop, optimize, validate, and deploy innovative computational methods for hit generation and lead design.

Responsibilities include selecting the right methods, communicating rationale, and contributing to workflows that enable rapid exploration of AI-generated

Qualifications

• Degree in relevant field with experience developing ML models related to chemical and biological data (10+ years for BS, 8+ for MS, 0+ for PhD).
• Experience with modern computational approaches for medicinal chemistry.
• Ability to implement, debug, and maintain computational tools in Python.

Responsibilities

• Consult with project team to establish desirable hit/lead criteria.
• Develop and maintain proficiency with cutting-edge computational methods used by the team.
• Identify and deploy the most suitable computational methods for project goals.
• Communicate rationale for methodologies to project teams.
• Contribute to workflows for computational hit generation and design of molecules.

Skills

ML/AI for chemistry

Python programming

Cheminformatics

Medicinal chemistry

Lead optimization

Education

BS in chemistry/CS/ML/cheminformatics/chemical engineering

MS in same fields

PhD in same fields

Tools

Python

Job description

AbbVie is seeking a scientifically skilled professional to advance AI-enabled drug discovery in our small molecule portfolio. You will collaborate with medicinal chemists, structural biologists, and chemoinformatics experts to identify, develop, optimize, validate, and deploy innovative computational methods for hit generation and lead design.

Responsibilities include selecting the right methods, communicating rationale, and contributing to workflows that enable rapid exploration of AI-generated