Join Our Team

We are seeking a post-doctoral fellow for our group.  The post-doc will develop his or her own project applying a variety of analytical models, including but not limited to deep learning techniques, to imaging (MRI and/or CT) and/or clinical (EHR) information to better understand and predict patient outcomes in a variety of neurological diseases.   There are also opportunities to understand variations in normal brain function across large neuroimaging datasets (especially the ABCD dataset) using deep learning or more traditional neuroimaging techniques.

The lab has developed a variety of analytical methods for segmenting and describing abnormalities on clinical brain MRI, which are applicable to a wide variety of neurological disorders.  In addition, techniques have been developed for quantitative analysis of clinical brain MRI across the spectrum of ages, including fetal brain MRI, infants, children, and adults.  We also leverage tools for assessing white matter microstructure using diffusion tensor imaging.

To qualify, a candidate must possess an MD or a PhD in engineering, computer science, neuroscience, or a related degree.  In addition, the candidate must have a background and/or strong interest in neuroscience, engineering, and/or computer science and must be excited to apply their skills to imaging of normal and pathologic brain structure.  Some familiarity with the Unix environment and compute clusters, as well as with the Python programming language, are requisites.  Strong interpersonal skills for interaction with other lab members, administrative and IT staff, and clinical staff are also required.  

The successful candidate will have the opportunity to work on independent projects supervised by the lab PI and will work in collaboration with other lab researchers/trainees.  Responsibilities may also include some supervision of junior staff research assistants and junior trainees.  Opportunities will include presentation at national/international conferences and participation in manuscript preparation/publication.  Start date is ASAP.

If interested, please email a resume/CV and cover letter to [email protected].

We are seeking a visiting scholar for our group. The scholar will either join an existing project or develop their own, applying a variety of analytical models, including but not limited to deep learning techniques, to imaging (MRI and/or CT) and/or clinical (EHR) information to better understand and predict patient outcomes in a variety of neurological diseases. There are also opportunities to understand variations in normal brain function across large neuroimaging datasets (especially the ABCD dataset) using deep learning or more traditional neuroimaging techniques.

The lab has developed a variety of analytical methods for segmenting and describing abnormalities on clinical brain MRI, which are applicable to a wide variety of neurological disorders. In addition, techniques have been developed for quantitative analysis of clinical brain MRI across the spectrum of ages, including fetal brain MRI, infants, children, and adults. We also leverage tools for assessing white matter microstructure using diffusion tensor imaging.

To qualify, a candidate must possess or be in the process of getting a MS in engineering, computer science, neuroscience, or a related degree. In addition, the candidate must have a background and/or strong interest in neuroscience as well as in engineering and/or computer science and must be excited to apply their skills to imaging of normal and pathologic brain structure. Familiarity with the Unix environment, as well as some experience with programming/coding, are requisites. 

The successful candidate will have the opportunity to work in collaboration with other lab researchers/trainees and participate in manuscript preparation/publication.

If interested, please email a resume/CV and cover letter to [email protected].