Instructor 1-Computational Imaging Scientist

The Office of Research at the University of South Florida (USF) Health Morsani College of Medicine seeks a Computational Imaging Scientist for a non-tenure earning Instructor I faculty appointment to support and advance multidisciplinary neuroimaging research. This research-focused faculty position will lead the development implementation and validation of advanced structural functional and diffusion MRI analysis methodologies. The individual will work closely with investigators across collaborating departments colleges and key stakeholders to support hypothesis-driven research grant development and translational research initiatives. The successful candidate will also develop an independent research program aligned with institutional priorities and contribute to the scholarly mission of USF Health.

• RESEARCH -Lead and support advanced processing and analysis of structural MRI functional MRI (fMRI) and diffusion-weighted imaging (DTI/DWI) data including surface-based and volumetric analyses. Develop optimize and maintain standardized imaging analysis pipelines using established and emerging neuroimaging platforms. Collaborate with faculty investigators to design imaging components of grant proposals submitted to NIH DoD and other funding agencies. Serve as Principal Investigator and/or Co-investigator on externally funded research projects. Integrate neuroimaging data with behavioral cognitive and clinical measures to support translational research. Prepare manuscripts for publications in peer-reviewed scientific journals and present research findings at national and international conferences. Ensure data integrity reproducibility and secure management of large-scale imaging datasets in compliance with institutional and regulatory policies.
• TEACHING -Supervise and mentor postdoctoral fellows graduate students residents and research trainees engaged in imaging and related research. Provide hands-on training in MRI data processing analysis methodologies and computational workflows for trainees and junior investigators. Participate in didactic teaching activities as appropriate including guest lectures workshops or formal coursework based on departmental and programmatic needs. Contribute to the academic development and career advancement of trainees through mentorship and scholarly guidance
• OTHER -Provide imaging science and data analysis support as part of the fMRI Research Cores shared research infrastructure. Participate in departmental college or university service activities consistent with faculty responsibilities. Contribute to interdisciplinary research teams core meetings and institutional initiatives that advance USF Healths research mission.
• Responsible to a Chair or other appropriate higher-level administrator of a State university.
• Responsible for teaching research service and related administrative activities.
• Responsible for academic advising and related activities.
• May represent the university college/school or department.

MINIMUM:

Minimum: PhD in Cognitive Neuroscience Neuroimaging Biomedical Engineering Neuroscience or a closely related field. Demonstrated expertise in neuroimaging data analysis including structural MRI fMRI and/or diffusion imaging. Proficiency in programming for imaging analysis (e.g. Python MATLAB and similar languages). Experience with widely used neuroimaging software platforms such as SPM FSL AFNI and FreeSurfer. Record of peer-reviewed publications commensurate with career stage. Ability to work collaboratively in multidisciplinary research environments. Preferred: Postdoctoral training in neuroimaging cognitive neuroscience or a related discipline. Experience developing or scaling automated imaging pipelines or computational workflows. Familiarity with statistical modeling machine learning or AI-enabled imaging approaches. Prior involvement in NIH DoD or other federally funded research projects. Demonstrated success or clear potential to obtain external research funding as a PI or co-Investigator. Experience working within shared research cores or large multidisciplinary research teams.