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Computational Associate


Job Location:

Boston, MA - USA

Monthly Salary: $ 41932 - 60340
Posted: 19 August 2026 (2 days ago)
Application Deadline: 16 November 2026
Vacancies: 1 Vacancy

Job Summary

Site: The General Hospital Corporation


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

Summary: The Research Data Analyst will work under the direction of the Principal Investigator to assist graduate students post-doctoral fellows clinical fellows and others with research projects that focus on analytical and computational needs.
Essential Functions: Provide direct assistance with experimental studies.
-Performs basic computational modeling and statistical analysis; prepares drafts of work for review; applies feedback received to create final analyses and/or reports.
-Meets with the PI and team to discuss work plans activities and results to support the applicability of efforts learning opportunities and professional development.
-Reviews collates and prepares standard analyses of medical record data.
-Perform administrative tasks such as required for data collection; prepare documentation and record-keeping; update databases; run reports.
-Conducts literature searches and submits appropriate articles to PI and team for consideration; identifies topics of interest for personal reading and may present at lab meetings.


Qualifications

Joint Urology-Pathology Research Laboratory Massachusetts General Hospital & Harvard Medical School

Drs. Chin-Lee Wu and Douglas Dahl are seeking a Computational Research Associate to join an interdisciplinary research team focused on advancing precision oncology through digital pathology artificial intelligence machine learning genomics and multi-omics research in genitourinary cancers.

This is an exciting opportunity to contribute to cutting-edge translational research at the intersection of computational pathology cancer biology human genetics and biomedical data science while collaborating with pathologists clinicians and researchers at Massachusetts General Hospital and Harvard Medical School.

Key Responsibilities

  • Develop and apply machine learning and computer vision models for digital pathology and whole-slide image analysis.
  • Analyze genomic transcriptomic epigenomic and spatial biology datasets.
  • Build computational workflows that integrate pathology images molecular data and clinical outcomes.
  • Support biomarker discovery and prognostic model development through multimodal data analysis.
  • Collaborate with a multidisciplinary team and contribute to scientific presentations manuscripts and publications.

Preferred Qualifications

  • Bachelors or Masters degree in Computer Science Bioinformatics Computational Biology Biomedical Engineering Statistics Data Science Genetics Epidemiology or a related quantitative field
  • Proficiency in Python and/or R programming
  • Experience with or strong interest in machine learning artificial intelligence bioinformatics computational biology or biomedical data science
  • Strong analytical organizational communication and collaboration skills
  • Experience with digital pathology whole-slide image analysis computer vision or medical imaging applications
  • Familiarity with deep learning frameworks such as PyTorch or TensorFlow
  • Experience analyzing genomics RNA sequencing spatial transcriptomics single-cell or epigenomic datasets
  • Experience integrating and interpreting multiple biological data modalities across complex research projects

Why Join Us

  • Work on innovative research combining AI digital pathology genomics and precision medicine.
  • Collaborate with world-class investigators at Massachusetts General Hospital and Harvard Medical School.
  • Gain hands-on experience with advanced computational and translational research methodologies.
  • Receive mentorship and opportunities for scientific authorship presentations and career development.
  • Contribute to discoveries that improve the understanding and treatment of cancer.

Education
Bachelors Degree Computational Biology required or Bachelors Degree Related Field of Study required

Experience
Experience as attained through education 0-1 year required

Knowledge Skills and Abilities
- Understanding of human pathophysiology hematologic function pregnancy physiology and related fields of study.
- Understanding of mathematical modeling including dynamical systems statistical analysis and computational methods.
- Ability to work collaboratively as part of a team and with supervision from team members.
- Ability to work productively with scientists and clinicians at all levels.
- Works in an organized manner with the ability to follow instructions processes and timelines.
- Can identify roadblocks occurring within areas of responsibility and refer them to the appropriate party(s) for assistance.
- Strong computer skills including accurate data entry.


Additional Job Details (if applicable)


Remote Type

Onsite


Work Location

55 Fruit Street


Scheduled Weekly Hours

40


Employee Type

Regular


Work Shift

Day (United States of America)



Pay Range

$41932.80 - $60340.80/Annual


Grade

5


At Mass General Brigham we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive and any offer extended will take into account your skills relevant experience if applicable education certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however it does not encompass all elements contributing to your total compensation addition to competitive base pay we offer comprehensive benefits career advancement opportunities differentials premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth. We invite you to apply and our Talent Acquisition team will provide an overview of your potential compensation and benefits package.


EEO Statement:

1200 The General Hospital Corporation 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 Veterans 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 .


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.


Required Experience:

IC


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Patients at Mass General have access to a vast network of physicians, nearly all of whom are Harvard Medical School faculty and many of whom are leaders within their fields.

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