Rsch Pro 5-Data Analytics

Data Governance, Pipelines & Technical Execution (40%) Ensure all external and multi-site dataset transfers strictly comply with fully executed Data Access Agreements (DAAs) before ingesting and storing data on local storage systems. Manage high-level data storage architecture, file directory organization, and data curation standards across local servers and high-performance computing (HPC) systems. Execute end-to-end neuroimaging data processing pipelines using Linux-based environments and specialized neuroimaging software (e.g., FSL, FreeSurfer, Connectome Workbench). Conduct Brain-Wide Association Studies (BWAS) estimations and related large-scale statistical associations. Implement statistical and computational harmonization methods across datasets, specifically utilizing techniques such as ComBat and functional connectivity residualizer approaches (fconn_residualizer). Apply advanced computational models including metamatching, transfer learning algorithms, and regularization techniques to derive predictive scores and robust brain-behavior mappings. Lead the development, maintenance, and feature expansion of the PNRS framework and associated repositories (e.g., GitHub) for internal and collaborative projects.

Scientific Writing, Dissemination & Grant Support (30%) Analyze complex neuroimaging and behavioral datasets across single-site and multi-site cohorts, evaluate statistical models, and synthesize results. Lead and co-author scientific manuscripts for publication in peer-reviewed journals. Assist faculty with grant preparation, progress reports, and research proposals for federally funded and foundation-sponsored projects. Present research findings at internal seminars, collaborative partner meetings, and external national/international scientific conferences.

Lab Coordination, Collaboration & Mentorship (30%) Serve as a technical point of contact for external collaborators and multi-site project teams utilizing PNRS or related analytical frameworks. Supervise, train, and mentor junior lab personnel, trainees, and students on data storage protocols, processing pipelines, quality control, and coding standard practices. Participate actively in lab and cross-project meetings, present analytical progress, and provide constructive technical feedback to team members and collaborators. Oversee data sharing protocols, research records management, and code distribution compliance in accordance with University policy and data-sharing agreements. Foster an inclusive, highly collaborative, and professional research environment.

Doctoral degree (Ph.D.) in Psychology, Biomedical Engineering, Neuroscience, Biostatistics, Data Science, or a related field, plus four years of relevant experience OR a BA/BS degree in a related field with at least six years of relevant advanced research experience. Demonstrated research experience combining quantitative behavioral analysis, neuroimaging, mathematical modeling, or computational neuroscience. Proven experience in data storage administration, data organization, and maintaining compliance with Data Access Agreements (DAAs). Hands-on experience with neuroimaging processing pipelines Demonstrated proficiency in data harmonization methods (e.g., ComBat, residualization techniques). Strong programming experience in languages and scientific platforms relevant to neuroimaging and big-data analytics (e.g., Python, MATLAB, R, Linux/Bash, C/C++)., Experience implementing machine learning, transfer learning, metamatching, or regularization strategies on neuroimaging/behavioral datasets. Advanced experience with functional and structural MRI processing pipelines (e.g., HCP pipelines, fMRIPrep, FSL, FreeSurfer, Workbench) and functional connectivity analysis Experience managing, harmonizing, or processing large public/consortium datasets (e.g., ABCD, UK Biobank, HCP) or collaborative multi-site imaging data. Experience developing and maintaining open-source software tools, version control systems (e.g., GitHub), and reproducible pipelines. Experience with resting-state functional connectivity (RSFC) and precision functional mapping. Strong interpersonal skills and a proven track record of working effectively within diverse, interdisciplinary, and multi-institutional research collaborations. A strong record of peer-reviewed publications and scientific writing experience. Background and interest in supervising junior colleagues Pay and Benefits

The University offers a comprehensive benefits package that includes:

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
• Low-cost medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and employer-paid life insurance
• Employee wellbeing program
• Excellent retirement plans with employer contribution
• Public Service Loan Forgiveness (PSLF) opportunity
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost
• Employee Transit Pass with free or reduced rates in the Twin Cities metro area

While our salary ranges provide a framework, it is important to note that most of the time, the initial pay may not reach the maximum of the range. This approach ensures that compensation reflects the value and unique contributions of each candidate while maintaining equity within our organization. As part of our commitment to fair and equitable compensation, please be aware that the salary offered to incoming candidates will be based on their individual credentials and experience.

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. About University of Minnesota

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.