Postdoc: AI-Driven Bioinformatics & Pharmacogenomics

Purdue University; West Lafayette (IN); On-site; USD 50,000 - 65,000; Full time

Job summary

Purdue University College of Pharmacy (Indianapolis campus) invites applications for a Postdoctoral Research Associate specializing in Bioinformatics, Pharmacogenomics, and AI/ML. The role offers collaboration with Regenstrief Institute and Indiana University to advance computational methods for precision therapeutics.

The ideal candidate has a Ph.D. in a related field and will lead independent and collaborative projects spanning omics data, knowledge graphs, NLP/LLM, and drug discovery, with

Qualifications

• Ph.D. in bioinformatics, biomedical informatics, computer science, pharmacogenomics, or related field.
• Strong programming skills in Python, R, SQL.
• Experience with omics data, pharmacogenomics, and biomedical ontologies is desirable.
• Proven ability to work in multidisciplinary teams and communicate research findings.

Responsibilities

• Lead and contribute to independent and collaborative projects across bioinformatics, pharmacogenomics, AI/ML, and deep learning.
• Analyze and integrate large-scale biomedical datasets including omics, pharmacogenomics, and clinical data.
• Build computational pipelines for drug discovery, drug response prediction, and precision therapeutics.
• Develop predictive models, knowledge graphs, NLP/LLM applications, and AI-enabled analytic frameworks.
• Lead manuscript preparation and contribute to grant proposals and scientific dissemination.
• Collaborate with clinicians, biomedical scientists, informaticians, and data scientists.

Skills

Python

R

SQL

Education

Ph.D. or equivalent degree

Job description

Purdue University College of Pharmacy (Indianapolis campus) invites applications for a Postdoctoral Research Associate specializing in Bioinformatics, Pharmacogenomics, and AI/ML. The role offers collaboration with Regenstrief Institute and Indiana University to advance computational methods for precision therapeutics.

The ideal candidate has a Ph.D. in a related field and will lead independent and collaborative projects spanning omics data, knowledge graphs, NLP/LLM, and drug discovery, with