Research Fellow - Deep Learning

Site: Massachusetts Eye and Ear Infirmary

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.

Job Summary

We have 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 on the development, testing and implement 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).

Qualifications

Postdoctoral Fellow in Deep Learning

We have 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 on the development, testing and implement 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 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 of clinical translation and patenting
• Presentation of the results at the scientific meetings and publication of journal articles
• Mentoring 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 with 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

Additional Job Details

Remote Type: Onsite

Work Location: 243-245 Charles Street

Scheduled Weekly Hours: 40

Employee Type: Regular

Work Shift: Day (United States of America)

EEO Statement

Massachusetts Eye and Ear Infirmary is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabili