Asst Manager / Deputy Manager - Cheminformatics &

About The Role

Design and implement computational workflows for chemical, biological, and multi-omics data analysis.
Apply cheminformatics techniques (virtual screening, molecular docking, QSAR, ADMET modeling) to support lead identification and optimization.
Analyze next-generation sequencing (NGS), RNA-seq, proteomics, and single-cell datasets to identify biomarkers, pathways, and novel targets.
Integrate chemical libraries with biological and clinical datasets for cross-domain insights.
Understanding of protein-protein interaction, ADC and PDC development.
Develop and apply machine learning/AI models for predictive drug discovery and biomarker discovery.
Collaborate closely with medicinal chemists, molecular biologists, pharmacologists, and data scientists.
Present findings through reports, visualizations, and presentations to internal and external stakeholders.
DbMS

Strong knowledge of drug discovery, molecular biology, and systems biology.
Proficiency in cheminformatics software (e.g., RDKit, Schrödinger, MOE, KNIME, Pipeline Pilot).
Hands-on experience with bioinformatics platforms and tools (Bioconductor, GATK, Galaxy, Cell Ranger).
Strong programming skills (Python, R, SQL, Bash); experience with ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn).
Familiarity with databases such as PubChem, ChEMBL, PDB, Ensembl, UniProt, and TCGA.
Knowledge of DBMS (e.g., MySQL, PostgreSQL, MongoDB) for managing and querying large-scale biological and chemical datasets.
Experience with HPC or cloud computing environments (AWS, GCP, or equivalent).
Excellent communication skills and ability to work in cross-functional teams.

Note: The interview process will include a presentation, where candidates must demonstrate an AI/ML model for drug discovery from their past experience.
Ph.D. or M. Pharm, M.Sc. in Cheminformatics, Bioinformatics, Computational Chemistry, Computational Biology, or a related field.