Massachusetts General Hospital (MGH) Department of Neurology and Harvard Medical School (HMS) is seeking a machine learning post-doctoral fellow for a full-time position applying time series and machine learning methods to uncover information in multimodal data collected from individuals with common and rare neurodegenerative diseases. Large and rapidly growing datasets include video, audio, wearable sensor, mobile device, and computer mouse data collected from individuals with common and rare neurodegenerative diseases. The candidate will become immersed in a multidisciplinary and collaborative environment, consisting of computer scientists, neurologists, clinical trials experts, and drug development teams, from varied groups in academia and industry. The candidate will additionally have the opportunity to collaborate on a recently launched, large open source initiative to advance the field of digital phenotyping in neurology ( This role is ideally suited for an individual with a rigorous training in time series methods, including recurrent neural networks, state space models, and Bayesian nonparametrics, and who wishes to understand and tackle important problems in neurology and healthcare. Individuals will be well positioned to pursue future opportunities in either academia or industry (pharma and tech) and work will be tailored to achieve these goals.


  • Develop and implement supervised machine learning approaches for classifying diseases and predicting disease severity and trajectory
  • Develop and implement unsupervised machine learning approaches for uncovering latent features and latent classes in neurodegenerative diseases
  • Develop pipeline for visualizing and modeling multimodal time series data. Creatively apply a broad range of methods, including HMMs, SSMs, Gaussian Processes, recurrent neural networks, and spectral analysis
  • Help frame cross-modal learning and data fusion problems to integrate information across multiple data types being collected in the lab
  • Engage collaborations within MGH Neurology as well as groups at Biogen, Harvard SEAS, MIT CSAIL, Broad Institute, Duke CS, and UMass Amherst CS
  • Form new academic and industry collaborations
  • Use coding best practices
  • Make methods and de-identified data widely available
  • Publish journal articles and present work at computer science and clinical conferences
  • Participate in grant writing and preparation
  • Work closely with the data collection team members, ensuring that data are being collected as expected and adjustments are being made to maximize the quality of the data
  • Work with data architects and data managers to develop scalable data analysis pipelines


  • Demonstration of the following characteristics: creative problem-solver, detail-oriented, highly organized, self-motivated, and able to work independently as well as within cross-functional teams
  • Exceptional written and oral communication skills
  • Ability to explain the essence of complex methods to non-technical audiences


Doctoral Degree required. 

Field of Study/Additional Specialized Training: A quantitative discipline such as computer science, engineering, math or physics.



•         Formal PhD training in computer science, physics, math, or related field.

•         Deep experience with several time series analysis methods, such as HMMs, SSMs, and GPs

•         Broad proficiency and experience with supervised and unsupervised machine learning methods

•         Experience building neural network architectures

•         Ability to work in Python environments


The postdoctoral fellow will work with a team of physicians, physician-scientists, computer scientists, and clinical research coordinators. Work will primarily be performed in a computational laboratory space on the MGH main campus, although regular meetings with collaborating groups in the Boston/Cambridge area are expected. On occasion work may be performed in MGH neurology clinic space or clinical research space at other locations at MGH in order to gain clinical exposure and better understand the data collection process. Travel to conferences and meetings to present research is expected. During the COVID-19 pandemic, most work will be conducted remotely, although members of the group have the opportunity to spend time in the lab space as well.EEO Statement Massachusetts General Hospital is an Equal Opportunity Employer.  By embracing diverse skills, perspectives and ideas, we choose to lead. Applications from protected veterans and individuals with disabilities are strongly encouraged.  

Primary Location

 MA-Boston-MGH CNY114 Boston

Work Locations

 MGH CNY114 Boston 114 16th Street  Boston 02129


 MD/PHD/Fellows/ PostDocs


 Mass General Physicians Organization(MGPO)


 Full-timeStandard Hours 40


 Day Job

Employee Status

 RegularRecruiting Department MGH Neurology Research

Job Posting

 Dec 4, 2020


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