Postdoctoral Fellow in Machine Learning and Computational Biology

Overview

The Daigle Lab of Bioinformatics and Systems Biology at the University of Memphis (UofM) is recruiting a postdoctoral fellow to develop and apply state-of-the-art machine learning methods to multi-omics data to identify biomarkers for post-traumatic stress disorder (PTSD). The successful applicant will join the Systems Biology of PTSD Biomarkers Consortium (SBPBC), a collaboration among UofM, NYU, Harvard, Brown, UCSF, ISB, and WRAIR.

The SBPBC has measured more than 1 million blood-based molecular markers in more than 13,000 individuals with and without PTSD. Members of the Daigle Lab have applied machine learning methods to these markers to enable PTSD diagnosis, prognosis, and clinical subtyping.

The postdoctoral fellow will lead efforts to develop novel machine learning models for integrating omics datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic) with relevant molecular pathways to enhance these capabilities. They will participate in publication and presentation of project findings, assist with funding proposals, and contribute to the training and mentoring of undergraduate and graduate trainees. The position offers opportunities for collaboration with SBPBC members and access to high-dimensional molecular datasets for cutting-edge ML method development.

• Lead development of novel machine learning models for integrating multi-omics data with molecular pathways to identify PTSD-related biomarkers.
• Publish and present project findings; assist with funding proposals.
• Contribute to training and mentoring of undergraduate and graduate trainees.
• Collaborate with SBPBC members and utilize high-dimensional molecular datasets for method development.

• Ph.D. in bioinformatics/computational biology, genetics/genomics, computer science, data science, or similar
• Strong publication record in peer-reviewed conferences and/or journals
• Experience applying machine learning methods (especially deep neural network approaches) to genome-scale datasets
• Extensive programming experience in R and/or Python (ideally both)
• Strong writing, communication, and interpersonal skills, including a proven ability to work both independently and as part of a team

This position is available for sponsorship consideration.

Applications must be submitted online at  and include a cover letter, CV, unofficial transcripts, two representative publications, and contact information for at least three professional references. For more information about the Departments of Biological Sciences, Computer Science, and the Daigle Lab, visit:

• https://(Use the "Apply for this Job" box below)./
• https:///
• .org

Informal inquiries can be sent to bjdaigle.

Hiring range:
Commensurate with experience
Posting Date: 05/05/2025
Closing Date:
Open Until Screening Begins:
Yes
Full-Time/Part-Time:
Full-Time