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Job Summary
Postdoctoral Fellow in Deep LearningWe 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.
Qualifications
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 (if applicable)
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 processingDevelopment and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disordersClinical translation and implementation of the developed algorithms and interactions with clinicians for their testingEstablishment of new and fostering of existing collaborationsParticipation in the regulatory aspects of clinical translation and patentingPresentation of the results at the scientific meetings and publication of journal articlesMentoring junior staffQualifications and Skills
PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fieldsBroad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architecturesExperience with neuroimaging data processingAdvanced 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 skillsStrong publication record and academic credentialsAbility to work effectively both independently and in collaboration with multiple investigators
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 Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
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