Translational Neuroscience Lab (PI: Michael Yassa) | University of California, Irvine
The Opportunity We are seeking an exceptional postdoctoral scholar to join the Yassa Lab and co-compete for the Hewitt Foundation Postdoctoral Fellowship (application in July 2026). The George Hewitt Foundation for Biomedical Research’s Postdoctoral Fellowship provides a fully funded three-year appointment with a competitive salary, benefits, and dedicated travel and research funds. Position is contingent upon fellowship award. This is not a standard postdoc posting. We are looking for a unique candidate – someone with a demonstrated track record of high-impact, first-author publications, superior technical command, and the drive to publish at an extraordinary pace. If you are the kind of scientist who thrives under pressure, moves fast without cutting corners, and wants to make a measurable dent in our understanding of the brain, read on.
What You'll Work On The lab focuses on the neurobiology of learning, memory, aging, and neuropsychiatric and neurodegenerative illness. You will work with large, deeply phenotyped datasets spanning structural MRI, resting-state and task fMRI, diffusion imaging, PET, EEG, multiomics fluid biomarker data, and extensive neuropsychological and cognitive assessments. Projects are organized around cross-functional teams and emphasize translational impact — connecting basic circuit-level mechanisms to biomarkers and clinical outcomes in neurodegenerative, neuropsychiatric, and related disorders.
Who You Are
Required qualifications: - Ph.D. in neuroscience, biomedical engineering, computer science, or a related quantitative field - Multiple first-author publications in peer-reviewed journals demonstrating exceptional writing ability - Advanced expertise in functional neuroimaging (resting-state connectivity, task fMRI analysis, network neuroscience approaches) - Strong programming skills in Python, R, and/or MATLAB, with demonstrated facility in building reproducible analysis pipelines - Hands-on experience applying AI/ML methods to neuroimaging or large-scale biomedical datasets - Comfort working with large datasets and high-performance computing environments
Strongly preferred: - Experience with diffusion imaging, EEG, or PET - Background in graph theory / network neuroscience - Familiarity with signal processing, bioinformatics, or computational modeling - Interest in or experience with clinical/translational research in neuropsychiatric or neurodegenerative populations - Track record of fellowship or grant writing (e.g., F31 NRSA, or equivalent)
The person, not just the CV: - Self-directed, relentlessly productive, and energized by hard problems - Collaborative and generous with colleagues - Resilient in the face of rejection and capable of absorbing tough feedback - Humble enough to be wrong, confident enough to lead - Fun to be around.
What We Offer - State-of-the-art equipment: 3T Siemens Prisma, 9.4T Bruker (rodent), Siemens Biograph Vision PET/CT, simultaneous fMRI/EEG, dedicated hybrid HPC cluster (CPU + GPU) - A deeply collaborative, high-output team environment - Active mentoring toward career development awards (K01, K99/R00) and independent faculty and industry scientist positions - A lab culture that is rigorous, irreverent, and genuinely enjoyable
Application Process This is a highly competitive position. The selection process involves multiple stages:
1. Initial application — Submit the following to Dr. Michael Yassa (myassa@uci.edu): - Cover letter with a detailed interest statement articulating your research vision and fit with the lab
- Full CV including a complete publication list
- Three letters of recommendation, one of which must be from your doctoral advisor and should specifically address the qualifications listed above
2. Interviews — Shortlisted candidates will participate in multiple rounds of interviews with the PI and lab members to assess scientific depth, interpersonal fit, and alignment with lab values.
3. Data analysis challenge — Finalists will complete a 72-hour timed data analysis project using a publicly available neuroimaging dataset. This exercise is designed to evaluate your technical capabilities in resting-state fMRI connectivity analysis and machine learning/classification approaches under realistic working conditions. Detailed instructions will be provided at the start of the challenge window.
The selected finalist will be nominated for the fellowship opportunity and will prepare a 2-page research statement in collaboration with Dr. Yassa. Review of applications begins immediately and will continue until the position is filled. Given the July 2026 Hewitt Fellowship deadline, early application is strongly encouraged.
About the Lab The Yassa Lab is a high-output, team-driven research environment. We work on hard problems with urgency. We hold each other to the highest standards of rigor and honesty. We also laugh a lot, share meals, and genuinely enjoy one another's company. If that sounds like your kind of place, we want to hear from you.
