Postdoctoral Associate

The Pitt Laboratory is seeking a highly motivated junior postdoctoral fellow to join our team and lead projects focused on extracellular vesicles in neuroinflammatory and neurodegenerative diseases. We conduct translational research aimed at understanding mechanisms of neurodegeneration in in multiple sclerosis (MS) and other inflammatory and neurodegenerative CNS disorders, with a strong emphasis on developing biofluid biomarkers that improve diagnosis, define disease heterogeneity, and can be implicated in clinical trials. A major complementary effort in the lab focuses on advanced histological and multiomic analysis of MS brain tissue to elucidate cellular and molecular mechanisms underlying demyelination and neurodegeneration.

The laboratory is embedded within a highly collaborative neuroimmunology program in the Department of Neurology at Yale School of Medicine, with close ties to genetics, computational biology, and clinical trial groups, including partnerships with pharmaceutical collaborators, who contribute clinical trial samples for ongoing exosome studies. The PI also co-directs the National Multiple Sclerosis Brain Bank, which provides unique access to well-characterized postmortem brain tissue.

Project focus

The successful candidate will contribute to an ongoing effort to:

· Isolate and characterize CNS-derived exosomes from blood and CSF in MS and MS-related diseases (MOGAD, NMOSD), ALS, long Covid and other CNS diseases.

· Apply multi-omic profiling (small and long RNA-seq, lipidomics) to define exosomal cargo signatures associated with different disease states.

· Develop and validate exosome-based biomarkers for treatment responses in ongoing interventional studies.

· Integrate exosome data with imaging and other fluid biomarkers using advanced computational tools.

Required qualifications

· PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field.

· Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis.

· Strong background in experimental design, quantitative data analysis, and scientific writing, evidenced by first-author publications.

· Ability to work both independently and collaboratively in a multidisciplinary team.

Appointment and application

The position is available for a minimum of 1 year with the possibility of extension, and compensation will be commensurate with experience and institutional guidelines. To apply, please email a single PDF containing your CV, a brief statement of research interests and relevant expertise, representative publications, and contact information for three references to [email protected]. Review of applications will begin immediately and continue until the position is filled.