Massachusetts Eye and Ear and Harvard Medical School

The Dystonia and Speech Motor Control Laboratory directed by Dr. Kristina Simonyan has an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection of the development, testing, and implementation of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech). 
Responsibilities will include but may not be limited to
•	Experimental data collection and processing
•	Development and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disorders
•	Clinical translation and implementation of the developed algorithms and interactions with clinicians for their testing
•	Establishment of new and fostering of existing collaborations 
•	Participation in the regulatory aspects for clinical translation and patenting
•	Presentation of the results at the scientific meetings and publication of journal articles
•	Mentoring of junior staff
 
Qualifications and Skills
•	PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fields
•	Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
•	Experience with neuroimaging data processing
•	Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
•	Knowledge and experience of the cloud-based computational platforms (e.g., AWS)
•	Excellent verbal and written communication skills 
•	Strong publication record and academic credentials
•	Ability to work effectively both independently and in collaboration with multiple investigators

Interested applicants should email a brief description of research background and career goals, and CV with a list of 3 references to Dr. Simonyan at [log in to unmask] and Dr. Battistella at [log in to unmask]