Job ID: 123301

PhD or Postdoctoral Position – Multi-omic bioinformatic processing of brain signatures

Position: Ph.D. Student

Deadline: 15 October 2025

City: Quebec

Country: Canada

Institution: Université Laval - CERVO Brain Research Center

Department: Department of Psychiatry and Neurosciences

Description:

PhD or Postdoctoral Position – Multi-omic bioinformatic processing of brain signatures
Labonté Laboratory, Department of Psychiatry and Neuroscience, Université Laval, Québec, Canada

The  Labonté Lab, in the Department of Psychiatry and Neurosciences at Université Laval, is seeking a highly motivated PhD student or postdoctoral fellow to join an exciting research program focused on the multi-omic integration of single cell epigenetic, proteomic and transcriptional signatures from human and mouse postmortem brain tissue in the context of depression and chronic stress.

The selected candidate will lead a project that leverages interspecies multi-omic single cell datasets. These datasets originate from human postmortem brain samples with a history of depression and from mouse models of chronic stress. The project will explore the molecular underpinnings of molecular signatures associated with major depression in human males and females and evaluate their correspondence in mouse models of stress across different longitudinal time points. The project involves processing raw epigenetic, proteomic and transcriptional single cell datasets and perform differential and network-based analyses. It will integrate cutting edge approaches in multi-omic integration from single cell and GWAS datasets and capitalize on recent progress in AI-based approaches to identify molecular interspecies signatures underlying the expression of depression and stress in males and females.

The project integrates a multidisciplinary toolkit, including:

  • Molecular processing for epigenetic, proteomic and transcriptomic single cell sequencing in mouse and human brain tissue.
  • Differential and network-based (WGCNA, MEGENA) analyses of human and mouse datasets.
  • Interspecies analyses of epigenetic, proteomic and transcriptomic single cell datasets.
  • Multi-omic integrative analyses of single cell epigenetic, proteomic and transcriptomic datasets.
  • Implementation of AI-based approaches to reveal multi-omic and interspecies molecular signatures underlying the development of emotional and depressive-like behaviors in males sand females.
  • Integration of an existing behavioral and functional expertise guiding follow up validation experiments

This position is part of an ongoing and well-supported research program with strong foundations in molecular, cellular, and systems neuroscience.

The Labonté Laboratory, located in the CERVO Brain Research Center and affiliated to Université Laval, offers a vibrant, collaborative, and multidisciplinary research environment with access to state-of-the-art facilities and expertise. The center also features a rich program of events, including weekly seminars and summer schools. We are strongly committed to the scientific and professional development of our trainees, offering ample opportunities for career advancement, networking, and training in both academic and translational neuroscience. We actively promote the principles of equity, diversity, and inclusion, and strive to create a supportive environment that welcomes individuals from all backgrounds and identities. The Labonté Laboratory is a fully bilingual environments and, while several options to learn French are available, the English language is prioritized in the lab.

The lab is located in Québec City, a historic and culturally rich city designated as a UNESCO World Heritage Site. The region offers a high quality of life and is surrounded by exceptional opportunities for outdoor activities year-round.

We are looking for candidates with:

  • A strong interest in the bioinformatic processing of omic datasets.
  • Demonstrated experience in programming and coding with Python, Matlab or R.
  • Experience in the processing of single cell datasets is considered an asset.
  • A high degree of scientific curiosity, motivation, and independence.

We encourage interested candidates to apply by sending an email to benoit.labonte@fmed.ulaval.ca including a motivation letter, CV, 2 reference letters and transcripts.