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Postdoctoral Fellow Positions in Multi-Modal Brain Imaging, Machine Learning, and Neural Modeling 

We have several open postdoctoral fellow positions to study normal and diseased organization of large-scale networks controlling highly skilled motor behaviors. We employ multi-modal neuroimaging methodologies, including task-production, resting-state, and pharmacological fMRI, high-resolution structural MRI, diffusion weighted imaging, and direct intracranial EEG to examine brain functional, effective and structural connectivity in healthy individuals, and patients with neurological disorders (dystonia and epilepsy). Our analytic approaches include, but are not limited to, graph theoretical analysis of large-scale neural networks, the application of novel machine learning algorithms for diagnostic and predictive classification of neurological disorders, and neural population modeling. In addition, we are examining the interplay between imaging, behavioral, and genetic factors that contribute to the pathophysiology of neurological disorders. 

The postdoctoral fellow will function as part of a multidisciplinary team of neuroscientists, geneticists, neurologists, laryngologists, and neurosurgeons at Mass. Eye and Ear, Mass General, and UMass Memorial Medical Center. Responsibilities will include the conduct of all aspects of the research protocol, such as the development, modification, and execution of data analysis, preparation of publications and scientific presentations, dissemination of the results through peer-reviewed scientific journals and at the major national and international meetings, and mentoring the junior staff. Excellent opportunities exist for various scientific interactions and collaborations with the experts in the fields of neuroscience, movement disorders, and genetics as well as for participation in the extensive programs of seminars, symposia, and other relevant meetings. 

The postdoctoral fellow may work on one or more projects. 

Dystonia 

(I) Machine learning for identification and validation of neuroimaging and genetic markers of dystonia and the prediction of risk for dystonia development.
(II) Graph theoretical analysis, machine learning, and pharmacogenomics for identification of primary mechanistic markers of action of a novel oral medication in patients with dystonia.
(III) Abnormalities of brain activation and neural network across different forms of task-specific focal dystonias using a combination of structural and functional neuroimaging techniques, genetic analysis, and clinico-behavioral neurotesting.

Epilepsy 

(I) Graph theoretical analysis of high-resolution intracranial EEG data for identification of the topology of large-scale neural connectivity in epilepsy and the development of neural markers for prediction of epileptic seizures. 

Normal Speech Production 

(I) The development and implementation of large-scale neural population models incorporating neurotransmission for simulation and prediction of brain activity during speech production.


Qualifications and Skills

  • PhD in neuroscience, mathematics, computer science, bioengineering, or related fields
  • Exceptionally strong computational and biostatistical skills to implement and integrate the analysis of multi-dimensional imaging, clinical, and/or genetic datasets
  • Solid experience in Python, MATLAB, and C
  • Strong experience in the algorithmic design, mathematical models (primarily stochastic differential equation systems), and analysis and integration of dynamic systems
  • Independent, self-motivated with a proven track record of productive research
  • Excellent verbal and written communication skills
  • Ability to work effectively both independently and in collaboration with multiple investigators
  • Strong publication record and excellent academic credentials


Position Duration

Full-time, 1-year initial contract, renewable annually contingent upon performance.


Salary

Commensurate with experience according to the Mass. Eye and Ear Policies and Procedures.


Deadline

The positions are available immediately and applications are considered on an ongoing basis until the positions are filled.


How to Apply

Applications should be sent to Dr. Kristina Simonyan at Kristina_Simonyan@meei.harvard.edu and should include the candidate’s CV with the list of publications, a statement of interest in the position, and the names and contact information of at least three professional referees.


Mass. Eye and Ear is an equal opportunity/affirmative action employer. We recognize the power and importance of a diverse employee population and strongly encourage applicants with various experiences and backgrounds.