Postdoc Research Fellow Pepin Lab
Postdoc Research Fellow Pepin Lab
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Job Description
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
The Pepin lab studies female reproductive development and diseases of the reproductive system such as infertility and ovarian cancer. The Pepin Lab is partnering with MITs Female Medicine through Machine Learning (FMML) to help develop individualized medicine for women by leveraging artificial intelligence (AI) and real-world health data to address gaps in female health research and care. Our mission is to transform disease discovery detection and delivery for women by developing open-source AI-driven solutions using diverse medical datasets including electronic health records (EHRs) and large biobanks such as UK Biobank and MGB Biobank.We seek a highly motivated Postdoctoral Fellow with demonstrated experience in machine learning applied to electronic health records and large-scale medical datasets (e.g. UK Biobank MGB Biobank). The successful candidate will contribute to FMMLs mission by developing and applying advanced AI methods to uncover novel insights in female health create disease detection tools and launch impactful clinical applications
The Postdoctoral Fellow will be expected to develop research methodologies to allow quantitative and qualitative evaluation and interpretation of data obtained. Participate in the interpretation of the results of experiments through conferencing with other senior lab personnel or principal investigator to review data compared to hypothesis and researches methodology in instances of inexplicable data. Collaborates with principal investigator in writing material for publication; may present papers or appear as principal or secondary author in publications and ensures Public Access policy is adhered to.
Duties will be performed in a research laboratory. This setting may create contact or exposure to one or more of the following: chemicals fluids sharp instruments and other supplies and equipment consistent with a research lab. Contact or exposure may be airborne or physical. Work schedule may be flexible and may require occasional evening weekend or holiday hours.
Qualifications
Duties and Responsibilities:
Design and implement machine learning models for analyzing EHRs and biobank data with a focus on sex-specific health outcomes and underexplored conditions in women
Develop predictive models and biomarkers (e.g. ovarian aging endometriosis and PCOS early detection) using multi-modal longitudinal and real-world data
Collaborate with a multidisciplinary team of clinicians data scientists and faculty to translate research into clinical tools and open-source resources.
Aggregate and analyze literature on sex differences in health to inform model development and support the creation of a comprehensive canon of female medicine
Prepare and submit research manuscripts for peer-reviewed publication and present findings at scientific conferences.
Mentor junior researchers and contribute to grant applications as needed.
Attends and may make presentations at lab meetings.
Structures lab operations; prioritizes and assigns work to lower level personnel; monitors quality and quantity of work performed and sees that standards are met and maintained.
Interprets the results of experiments through conferencing with senior lab personnel or principal investigator to review data compared to hypothesis and researches methodology in instances of inexplicable data. Organizes and summarizes acquired data using scientific and statistical techniques.
Collaborates with principal investigator in writing material for publication; may present papers or appear as principal or secondary author in publications and ensures Public Access policy is adhered to.
May teach moderately difficult-to-complex analyses to students and research personnel.
May provide functional guidance to personnel and trainees.
Prudent use of hospital resources expected.
Performs other duties as assigned.
Skills/Abilities/Competencies Required
Ph.D. (or equivalent) in biomedical informatics computer science statistics computational biology or a related field
Hands-on experience with machine learning and deep learning applied to EHRs and large medical datasets (e.g. UK Biobank MGB Biobank)
Proficiency in programming languages commonly used in data science (e.g. Python R) and deep learning frameworks (e.g. PyTorch TensorFlow)
Strong analytical scientific writing and communication skills.
Demonstrated ability to work collaboratively in multidisciplinary teams.
Experience with medical ontologies and/or causal inference in healthcare datasets
Familiarity with sex-specific health issues womens health research or interest in advancing equity in medical AI
Experience with federated learning time-series modeling or multi-modal data integration is a plus
Strong publication record in relevant fields
Education/Experience
Ph.D. (or equivalent) in biomedical informatics computer science statistics computational biology or a related field
At least one year of hands-on experience with machine learning and deep learning applied to EHRs and large medical datasets or equivalent (e.g. UK Biobank MGB Biobank).
Additional Job Details (if applicable)
Additional Information:
Interested applicants should submit:
Curriculum Vitae (including links to academic webpages and code repositories if available)
Two representative publications
Statement of research experience and future plans (max 2 pages)
Contact information for three references
To apply for this position please email or send your resume to:
David Pepin PhD
185 Cambridge Street
CPZN 6-100
Boston MA 02114
Remote Type
Work Location
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham our competency framework defines what effective leadership looks like by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance make hiring decisions identify development needs mobilize employees across our system and establish a strong talent pipeline.
Employment Type
Full-Time
