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UCSF (San Francisco, CA USA) Developmental Cognitive & Educational Neuroscience Lab, under the direction of Fumiko Hoeft, is seeking to hire a research scientist and/or postdoctoral fellow for a minimum commitment of two-years. We are seeking a researcher who has strong interests and skill-sets in applying machine learning algorithms to large multi-site and complex neuroimaging and possibly genetic datasets. Topics of research will be on dyslexia, motivation and learning, academic ability, and healthy brain development. RECENT PUBLICATIONS: 1. Hoeft et al. Arch Gen Psychiatry (in press) -- Brain basis of hypnotizability using resting-state fMRI, DTI and T1 aMRI. 2. Hoeft et al. PNAS (2011) -- Predicting outcome of dyslexia using imaging and machine learning algorithms. 3. Tanaka Black et al. Psychol Sci (2011) -- Role of IQ in reading using machine learning algorithms and 2 fMRI datasets. 4. Hoeft et al. Arch en Psychiatry (2011) -- Examination of autism and fragile X toddler aMRI using supervised and unsupervised learning methods. 5. Hoeft et al. PNAS (2010) -- Longitudinal structural brain development in typical toddlers, toddlers with developmental delay and toddlers with fragile X syndrome. CURRENT COLLABORATORS: Jessica Black (Boston College), Carol Dweck (Stanford), Gary Glover (Stanford), Elena Grigorenko (Yale), Ken Pugh (Yale/Haskins Laboratory), John Gabrieli (MIT), and Bruce McCandliss (Vanderbilt University).

Additional information

MDs, PhDs, or equivalent are encouraged to apply. In rare instances, individuals with a MSc will also be considered. The position can begin immediately.

Apply for job

Interested candidates should email Dr. Hoeft (fumiko.hoeft@ucsf.edu) with a cover letter and CV. Please add [UCSF job] and your full name in the Subject of email. Qualified candidates will be asked to have 3 letters of reference forwarded to Dr. Hoeft.