Research Fellow, PGY0 (Zebardast) at Mass. Eye and Ear (MEE) in Boston, Massachusetts

Job Description:

We are seeking a highly qualified and motivated postdoctoral fellow to join our collaborative teams in the Department of Ophthalmology / Glaucoma division at Massachusetts Eye and Ear (MEE), Harvard Medical School, to work on innovative projects that utilize machine learning and data science to understand mechanisms of glaucoma, a common eye disease.


The successful candidate should have an MD or PhD in a relevant field such as biostatistics, computer science, machine learning or a related quantitative field, and will be interested to apply and develop computational and statistical methods for analyzing large-scale clinical, imaging and genomic data. The ideal candidate will have strong programming skills, a solid statistical understanding, and experience with large-scale data analysis, and will be excited to contribute to advancing the scientific discovery and medicine of eye disease.


The candidate will work with Dr Zebardast as part of a vibrant research community of clinician scientists, biostatisticians, computational biologists, and machine learning engineers at MEE, an international leader for treatment and research in Ophthalmology and Otolaryngology. Being a member of our group will provide the opportunity to contribute to impactful projects and large collaborative efforts in the field of ocular data science. To learn more about our lab research directions please visit:


If interested, please send your CV, a cover letter describing your previous research experience and future research interests, and contact information for 3 references, to Dr. Nazlee Zebardasrt : Nazlee_Zebardast [at] meei.harvard.edu.



CHARACTERISTIC DUTIES:

• Work both on independent and collaborative ophthalmic data science projects


• Critically review, analyze, and communicate results to our team and collaborators.


• Summarize work for publications and presentations


• Organize all scripts in a publicly available repository (e.g., github) with clear documentation.

Qualifications

• Possess an MD or PhD preferably with a background in mathematics, computational science, computer science, statistics, machine learning, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.


• Strong programming skills and in-depth experience with several programming languages required, e.g. Python, R, C++; Experience with Cloud Computing a plus.


• Experience with Unix/Linux environments, including shell scripting


• Research experience with large-scale data analysis


• Have a strong and productive publication record.


• Demonstrate critical thinking, rigorous work, and ability to meet deadlines.


• Strong personal skills, and excellent organization and verbal and written communication skills.


• Ability to work effectively both independently and collaboratively in a fast-paced, academic environment and evolving field.

WORKING CONDITIONS:



The Zebardast lab is located in the main hospital building of Mass Eye and Ear, 243 Charles Street, in a research and office workspace that is part of MEE. The postdoctoral fellow will work in an office space adjacent to other biostatisticians and students and will be part of a larger multidisciplinary research environment. There is convenient access to MEE cafeteria on the 7th floor and, more importantly, abundant opportunities to interact with other MEE research groups and the Medical and Population Genetics community at the Broad Institute. The position will be hybrid with both remote and in-person components.



PHYSICAL REQUIREMENTS:



None.



EEO Statement

Massachusetts Eye and Ear is proud to be an equal-opportunity employer and is committed to providing a workplace free from harassment or discrimination. All employment decisions are made without regard to race, color, age, gender, gender identification, sexual orientation, religion, marital status, sex, pregnancy or conditions related to pregnancy, national origin/ancestry, citizenship, disability, military status, genetic information, or any other basis prohibited by law. These protections extend to all management practices and decisions, including recruitment and hiring practices, appraisal systems, promotions, training, and career development programs Apply Now