Computational Medicinal Chemist – Drug Discovery
Job Description
We are seeking a Computational Medicinal Chemist to support drug discovery programs. The candidate will focus on in silico design, optimization, and evaluation of small molecules, integrating insights from structural biology and bioinformatics to accelerate lead identification and optimization.
Key Responsibilities:
Apply RDKit for cheminformatics and use ADMET prediction tools to guide compound selection.
Analyze SAR (structure-activity relationships) and prioritize compounds using QSAR/QSPR modeling.
Design and optimize small molecules using computational approaches.
Collaborate with structural biologists and bioinformaticians to interpret protein-ligand interactions.
Develop and maintain computational pipelines and workflows for drug discovery projects.
Qualifications:
Master’s or Ph.D. in Computational Chemistry, Medicinal Chemistry, organic chemistry or a related field.
2–5 years of experience in computational medicinal or organic chemistry for drug discovery.
Skills in molecular modelling software docking, and virtual screening.
Preferred Skills:
Knowledge of cheminformatics, drug-likeness, and ADMET prediction. Experience in multi-disciplinary computational drug discovery projects. Experience with ML/AI-assisted drug design.