Computational Medicinal Chemist

What you'll do

• Apply structure- and ligand-based design, SAR, and predictive methods to guide medicinal chemistry and assess drug properties.
• Develop and apply machine learning, active learning, and physics-based CADD models, including models using screening and imaging data.
• Collaborate on target identification, lead optimization, candidate nomination, and mechanistic studies across drug discovery programs.

What they ask for

• PhD in medicinal chemistry, computational chemistry, cheminformatics, computational biology, computational chemical biology, or a related field; laboratory-based chemistry or biology candidates with strong computational experience are also encouraged.
• Familiarity with computational drug design tools, high-performance computing environments, and a strong peer-reviewed publication history.
• Strong communication and data visualization skills; demonstrates rigor, diligence, adaptability, and team orientation.

Nice to have

• Related post-graduate experience preferably on drug discovery project teams.
• Proven innovation through analogue design with significant impact on discovery projects.

Pay

$126,000 and $234,000 USD annually (base salary); $126,000.00 - $234,000.00 (base salary)

Tools

machine learning, active learning, physics-based CADD, Schrdoinger, CCG, OpenEye, Python (Programming Language), Deep Learning

AI focus

Applies machine learning, active learning, and predictive modeling to small-molecule drug discovery, including induced proximity and high-content, time-resolved screening and imaging data.