The Neural Plasticity and Neurorehabilitation Laboratory (NPNL) of the University of Southern California, directed by Dr. Sook-Lei Liew, is now looking for an Assistant Professor of Research. The laboratory is devoted to the study of neuroplasticity and motor learning in healthy individuals and individuals after stroke. The overall aim is to understand mechanisms of brain plasticity and to apply this knowledge to the development of novel interventions to enhance motor recovery after stroke. The laboratory utilizes big data neuroimaging (structural, diffusion, and functional MRI) and neuroinformatics methods, along with brain computer interfaces and non-invasive brain stimulation techniques, such as transcranial magnetic stimulation (TMS) and transcranial electric stimulation (tES, including tDCS, tAS, and tRNS). More information about the NPNL can be found at https://chan.usc.edu/npnl.
Responsibilities of this role include writing code to translate experimental procedures into reproducible and scalable workflows, developing validation scripts and pipelines to ensure the accuracy and reliability of outputs, and designing processes to record, manage, and analyze metrics within a database. The candidate will also conduct and support research at the intersection of neuroscience, data science, and neurorehabilitation, contributing to the advancement of ongoing projects in the lab. In addition, the researcher will assist with the preparation of manuscripts for publication and help manage day-to-day lab operations under the supervision of the principal investigator.
The ideal candidate should have a doctoral degree in a relevant scientific discipline (neuroscience, engineering, computer science) and at least one year of postdoctoral fellowship experience. The successful applicant should be highly motivated, organized, and quick to learn, as well as possess strong written and verbal communication skills. A strong background in computer programming, database management, data acquisition, processing, validation, visualization, and analysis, in addition to technical knowledge with multiple programming languages (Python, Bash, C, C++, C#, R) and version control (git, GitHub) is preferred. Experience with training and applying machine learning, deep learning, AI or large language models, particularly to stroke neuroimaging data, is preferred.
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The salary rate range for this position is $85,000 – $95,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and 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.
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