UCSF (San Francisco, CA USA)'s newly established Developmental Cognitive & Educational Neuroscience Lab, under the direction of Fumiko Hoeft, is seeking to hire a postdoctoral fellow for a minimum commitment of two-years.
We are seeking a researcher who has strong interests and background in applying machine learning algorithms to large multi-site and complex neuroimaging and possibly genetic datasets.
TOPICS INCLUDE BUT ARE NOT LIMITED TO: dyslexia, motivation and learning, academic ability, and healthy brain development.
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 toddlers' 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.
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).
ELIGIBILITY AND APPLICATION INFO:
MDs, PhDs, or equivalent are encouraged to apply. In rare instances, individuals with a MSc will also be considered. The position can begin immediately.
Interested candidates should email Dr. Hoeft ([log in to unmask]<mailto:[log in to unmask]>) 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.
Fumiko Hoeft MD PhD
Email: [log in to unmask]<mailto:[log in to unmask]>