Mass General Brigham is looking to solve the problem of automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes using machine-learning algorithms.
Requirements
- 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 with cloud-based computational platforms (e.g., AWS)
- Strong publication record and academic credentials
- Ability to work effectively both independently and in collaboration with multiple investigators
Responsibilities
- 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 of clinical translation and patenting
- Presentation of the results at the scientific meetings and publication of journal articles
- Mentoring junior staff
Other
- Excellent verbal and written communication skills
- Ability to work effectively both independently and in collaboration with multiple investigators
- Strong publication record and academic credentials
- Onsite work location
- 40 scheduled weekly hours
