Postdoctoral Associate – The Getz Lab, Multiple Myeloma – Machine Learning
About The Position
The Getz Lab at the Broad Institute and Massachusetts General Hospital seeks a computational postdoctoral associate to lead development of an AI-driven prediction model for multiple myeloma. The model will integrate multimodal information, including whole-genome sequencing, single-cell transcriptomics, immune profiling, and clinical data, to identify patients likely to respond to therapy or develop resistance. The work is expected to take place over two years, with potential follow-on work, in close collaboration with Dr. Irene Ghobrial’s laboratory at Dana-Farber Cancer Institute. The role bridges computational biology, machine learning, and clinical research, with the goal of improving understanding of disease progression, therapeutic response, and resistance and supporting precision treatment decisions. The successful candidate will join an interdisciplinary and collaborative research group of scientists, engineers, and clinicians. The lab emphasizes intellectual rigor, shared ideas, mentoring, and educational and skill-building opportunities. The position offers opportunities to develop computational and statistical expertise, contribute to cancer research, and potentially teach and mentor junior team members.
Requirements
- PhD in Bioinformatics, Computer Science, Machine Learning, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline.
- 0–1+ years of post-graduate experience.
- Demonstrated experience developing and validating machine learning models.
- Experience with computational analysis, algorithm development, and statistics.
- Proficiency in at least one modern programming language.
- Ability to collaborate on projects with bioinformaticians, wet-lab experimentalists, and clinicians.
- Demonstrated ability to conduct rigorous and reproducible research in a fast-paced environment.
- Ability to learn quickly; analytical thinking, creativity, a hands-on approach, and teamwork.
- Strong oral and written communication skills.
- Inclination to acquire knowledge of cancer genomics.
Nice To Haves
- Experience with a scientific programming environment such as Python, R, or Matlab.
- Prior experience applying AI/ML methods in cancer.
- Knowledge of cancer genomics.
Responsibilities
- Lead the design and execution of data analysis strategies for research projects, especially AI-driven prediction models in multiple myeloma.
- Explore and help design tools for analyzing novel data types.
- Conceive, implement, and test statistical models and analyze experimental data.
- Present results to audiences that include non-computational researchers.
- Prepare written reports, such as manuscripts, grants, and patents, and presentations for meetings.
- Teach and mentor junior team members as opportunities arise.
- Collaborate with scientists, engineers, clinicians, bioinformaticians, and wet-lab experimentalists.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401(k) retirement plan
- Flexible spending and health savings accounts
- At least 13 paid holidays
- Winter closure
- Paid time off
- Parental and family care leave
- Employee assistance program
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
