The Neural Plasticity and Neurorehabilitation Laboratory (NPNL) of the University of Southern California, directed by Dr. Sook-Lei Liew, is now looking for a highly motivated Research Lab Technician II.
The laboratory focuses on using data science and AI approaches to neuroimaging and genetics, using large-scale structural MRIs and behavioral datasets to examine brain-behavior relationships after stroke. The lab also participates in national clinical trials using brain stimulation (e.g., transcranial magnetic stimulation (TMS)) and telerehabilitation to predict and improve stroke outcomes. Research will entail working with a number of research partners worldwide. More information about the NPNL can be found at http://npnl.usc.edu.
The ideal candidate should have, or will soon have, a bachelor’s or higher degree in Neuroscience, Computer Science, Biomedical Engineering, or a related field. The successful applicant should be highly motivated, organized, willing to learn, adaptable, detail-oriented, possess strong written and verbal communication skills, and takes initiative. Technical knowledge of neuroimaging and brain anatomy, extensive experience with organizing, maintaining and analyzing large brain imaging datasets, programming expertise with python, Bash and cloud computing, experience with Brain Imaging Data Standards (BIDS) and structural MRI—based neuroimaging software programs (e.g., FreeSurfer, ITKSna) and statistics/machine learning strongly preferred.
This position is a full-time, one-year (renewable) position, and can start as early as August 2026.
The hourly rate ranges from $25.71 - $31.30. When extending and offer of employment, the University of Southern California considers factors such as (but not limited to) the scope of responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.
Minimum Education: Associate's degree, Specialized/technical training, Combined experience/education as substitute for minimum educationMinimum Experience: 2 years
Minimum Field of Expertise: Working knowledge of laboratory equipment and research protocols. Knowledge of computer analysis techniques and ability to provide routine analysis and interpretation of research data.
USC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC observes affirmative action obligations consistent with state and federal law. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to the Background Screening Policy Appendix D for specific employment screen implications for the position for which you are applying.
We provide reasonable accommodations to applicants and employees with disabilities. Applicants with questions about access or requiring a reasonable accommodation for any part of the application or hiring process should contact USC Human Resources by phone at (213) 821-8100, or by email at [email protected]. Inquiries will be treated as confidential to the extent permitted by law.
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If you are a current USC employee, please apply to this USC job posting in Workday by copying and pasting this link into your browser:
https://wd5.myworkday.com/usc/d/inst/1$9925/9925$152088.htmldSkills Required
- Associate's degree, specialized or technical training, or equivalent combined experience and education
- At least 2 years of experience
- Working knowledge of laboratory equipment and research protocols
- Knowledge of computer analysis techniques
- Ability to provide routine analysis and interpretation of research data
- Bachelor's or higher degree in Neuroscience, Computer Science, Biomedical Engineering, or a related field
- Technical knowledge of neuroimaging and brain anatomy
- Experience organizing, maintaining, and analyzing large brain imaging datasets
- Programming expertise with Python and Bash
- Experience with cloud computing
- Experience with Brain Imaging Data Standards and structural MRI neuroimaging software
- Experience with statistics and machine learning
- Strong written and verbal communication skills
- Organized, adaptable, detail-oriented, motivated, willing to learn, and able to take initiative
