Summary
Purdue University’s College of Engineering is seeking a highly motivated Postdoctoral Fellow to join a groundbreaking project titled “Beyond Functional Connectivity: Disentangling Neural and Hemodynamic Network Dysfunction in Alcohol Use Disorder.” This project aims to establish a systems-level framework for Alcohol Use Disorder (AUD) by moving beyond conventional functional connectivity. The fellow will disentangle neural-network organization, systemic/cerebrovascular physiology, and their interaction in resting-state fMRI. Leveraging expertise in BOLD physiology, lag-aware modeling, functional connectomics, and network science, the research will create two layers of representation for each participant—a neural functional network and a hemodynamic propagation network—to quantify their cross-layer coupling. The ultimate goal is to identify novel AUD phenotypes, such as reduced neural–hemodynamic alignment, which could have transformative implications for understanding and treating AUD, with broader applicability to aging, neurodegeneration, and pain.
Postdoctoral Fellow: Disentangling Neural and Hemodynamic Network Dysfunction in Alcohol Use Disorder
Designation
Postdoctoral Fellow
Research Area
- Alcohol Use Disorder (AUD)
- Neuroimaging (fMRI, resting-state fMRI)
- Network Neuroscience
- Cerebrovascular Physiology
- Computational Neuroscience
- Biomedical Engineering
Location
Purdue University, West Lafayette, IN
Eligibility/Qualification
Candidates must possess a PhD in one of the following fields or a closely related area:
- Biomedical Engineering
- Neuroscience
- Computational Neuroscience
- Applied Mathematics
- Computer Science
- Statistics
Required Experience and Skills:
- Strong experience analyzing resting-state fMRI data, including preprocessing, quality control, nuisance regression, and functional-connectivity estimation.
- Knowledge of BOLD physiology, cerebrovascular effects, systemic low-frequency oscillations, or physiological-noise modeling.
- Experience with lag-aware analysis, time-delay estimation, signal propagation, or related time-series methods.
- Expertise in network neuroscience, including connectome construction, graph measures, community detection, gradients, and spectral methods.
- Familiarity with dynamic functional connectivity and multilayer or multimodal network analysis.
- Strong quantitative background in statistical modeling, multivariate analysis, dimensional phenotyping, and correction for multiple comparisons.
- Experience using spatial null models and accounting for cortical geometry and spatial autocorrelation.
- Proficiency in Python, MATLAB, R, or comparable scientific-computing environments.
- Ability to develop reproducible analytical pipelines for large neuroimaging datasets.
- Experience with tools such as FSL, AFNI, SPM, FreeSurfer, fMRIPrep, Nilearn, or comparable software.
- Ability to integrate physiological, imaging, demographic, and behavioral data.
- Strong scientific writing and visualization skills, with evidence of peer-reviewed publications.
- Commitment to open science, including documented code, version control, data provenance, and reproducible reporting.
- Capacity to work independently while collaborating effectively across neuroimaging, physiology, network-science, and clinical teams.
Desirable Experience and Skills:
- Familiarity with Riemannian geometry, covariance-based representations, or geometry-aware distances.
- Experience with substance-use, psychiatric, or behavioral phenotyping—particularly alcohol use disorder.
- Interest in translating methodological developments beyond AUD to aging, neurodegeneration, pain, and other health conditions.
Job Description
The Postdoctoral Fellow will be responsible for:
- Developing and applying advanced analytical techniques to resting-state fMRI data.
- Utilizing expertise in systemic low-frequency BOLD physiology and lag-aware modeling to extract subject-specific hemodynamic components (oscillation amplitudes, delay maps, propagation gradients, and physiological contributions).
- Constructing conventional and physiologically corrected connectomes using functional connectomics and network science principles.
- Quantifying cross-layer coupling between neural functional networks and hemodynamic propagation networks using geometry-aware distances, gradient and community alignment, spectral similarity, and spatial null models.
- Investigating associations between observed abnormalities and various AUD-related factors (alcohol consumption, problems, family history, impulsivity, age, sex, education).
- Working collaboratively with co-advisors Dr. Joaquín Goñi (Industrial Engineering) and Dr. Yunjie Tong (Biomedical Engineering).
- Contributing to peer-reviewed publications and presentations.
- Adhering to open science principles for reproducible research.
This position is part of the prestigious Lillian Gilbreth Postdoctoral Fellowships at Purdue Engineering.
How to Apply
Further details on the application process for the Lillian Gilbreth Postdoctoral Fellowships can be found on the Purdue Engineering Research website. Interested candidates should prepare a detailed CV, a cover letter outlining their research interests and relevant experience, and contact information for professional references. Please reference the project title “Beyond Functional Connectivity: Disentangling Neural and Hemodynamic Network Dysfunction in Alcohol Use Disorder” in your application.
Last Date for Apply
Open until filled
Apply Link
Please visit the official Purdue Engineering Research website for Gilbreth Fellowship applications: Purdue Engineering Gilbreth Fellowships
