JOB DESCRIPTION:

We seek a postdoctoral researcher skilled in computational biology, machine learning, and network pharmacology to integrate multimodal datasets from reproductive pharmacology—drug testing, PBPK modeling, and protein interaction studies—into predictive and mechanistic models.

MINIMUM QUALIFICATIONS:

Ph.D., M.D. or Doctoral equivalent in any field. Scientific research experience

PREFERRED QUALIFICATIONS:

• Ph.D. in Bioinformatics, Computational Biology, Systems Pharmacology, or related field.
• Proficiency in Python, ML frameworks (scikit-learn, TensorFlow, XGBoost), and network biology tools (Cytoscape, NetworkX).
• Experience with PBPK models, ADMET prediction, or omics data integration preferred.
• Ability to link computational outputs with experimental insights.
• Background in pregnancy PK, feto-maternal interface biology, or protein-protein interactions.
• Familiarity with AutoDock, DeepChem, or exosome databases.
• Experience curating training datasets from literature/experiments.

Please refer the Job description for details