Postdoctoral Research Associate - Bioinformatics, Pharmacogenomics, and AI/Machine Learning

FLSA Status

Exempt

Job Summary

A Postdoctoral Research Associate position is immediately available for a highly motivated, independent, and ambitious candidate in the Department of Pharmacy Practice at Purdue University College of Pharmacy (Indianapolis campus). This position offers extensive collaborative research opportunities with the Regenstrief Institute and Indiana University. The successful candidate will work closely with faculty, scientists, clinicians, informaticians, health professionals, and trainees across institutions to develop and apply computational methods for biomedical discovery and precision therapeutics.

This position is ideal for candidates seeking advanced training and leadership opportunities in bioinformatics, pharmacogenomics, artificial intelligence, machine learning, computational drug discovery, and precision medicine.

Research Areas: The postdoctoral fellow will contribute to projects in one or more of the following areas:

• Bioinformatics and computational biology

• Multi-omics data integration and analysis

• Pharmacogenomics and computational drug discovery

• Pharmacogenomics and precision medicine

• AI and machine learning applications in biomedical research

• Deep learning and predictive modeling

• Natural language processing and large language models for biomedical data

• Drug response prediction and treatment optimization

• Biomedical knowledge graphs and network medicine

• Translational data science for therapeutic discovery

Primary Responsibilities: The Postdoctoral Research Associate is expected to lead and contribute to independent and collaborative research projects, including but not limited to:

• Developing and applying bioinformatics, pharmacogenomics, AI, machine learning, and deep learning methods

• Analyzing and integrating large-scale biomedical datasets, including omics, pharmacogenomics, medication, drug database, ontology, knowledge graph, and clinical molecular data

• Building computational pipelines for drug discovery, drug response prediction, therapeutic target identification, and precision therapeutics

• Developing predictive models, knowledge graphs, NLP/LLM applications, and AI-enabled analytic frameworks

• Leading manuscript preparation and contributing to grant proposals and scientific dissemination

• Collaborating with multidisciplinary stakeholders, including clinicians, biomedical scientists, informaticians, and data scientists

Core Qualifications

1. Ph.D. or equivalent degree in a related field, such as bioinformatics, biomedical informatics, computer science, computational biology, biostatistics, pharmacogenomics, biomedical engineering, health data science, or a related discipline

2. Demonstrated research experience in one or more of the following areas: bioinformatics; pharmacogenomics; artificial intelligence; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine

3. Strong programming skills in Python, R, SQL, or related languages

4. Experience with omics data, pharmacogenomics data, drug databases, biomedical ontologies, knowledge graphs, or large-scale biomedical datasets is highly desirable

5. Strong written and oral communication skills, with evidence of scholarly productivity, including peer-reviewed publications or conference presentations

6. Ability to work effectively with diverse multidisciplinary teams, including clinicians, biomedical scientists, informaticians, and data scientists

Application Materials:

1. Curriculum Vitae

2. Cover letter explaining research interests, relevant experience, and career goals

3. Contact information for 2–3 references

Contact

Serena Guo, MD, PhD

William S. Bucke Associate Professor, Department of Pharmacy Practice, Purdue University College of Pharmacy

Investigator, Regenstrief Institute

[email protected]

Purdue University is an equal opportunity/equal access university.