Postdoc Computational Biologist (Data Science/ML)

TL;DR

Postdoc Computational Biologist (Data Science/ML): Leading computational analysis for projects exploring disease mechanisms in multiple myeloma with an accent on spatial multi-omics data analysis. Focus on developing new spatial and genomic analysis methodologies for integrating data and predicting tumor outcomes.

Location: On-Site in Cambridge, MA

Salary: $70,000.00/yr - $92,666.67/yr

Company

The Getz Lab (at the hirify.global and MGH) is a world-leading laboratory for cancer genome analysis, developing computational methods to study the molecular basis of cancer.

What you will do

• Play a lead role in designing and executing data analysis strategies, especially for spatial multiomics data.
• Drive the project's scientific vision, identifying key biological questions and spearheading computational strategies.
• Explore and develop tools for analyzing novel data types.
• Develop new spatial and genomic analysis methodologies for integrating data and predicting tumor outcomes.
• Conceive, implement, and test statistical models; analyze data from experiments.
• Prepare written reports and presentations for meetings.

Requirements

• A PhD in Bioinformatics, Computer Science, Machine Learning, or a related quantitative discipline.
• 0-1+ years of post-graduate experience.
• Experience with computational analysis, algorithm development, and statistics.
• Sufficient hands-on experience in methods to analyze spatial multi-omic data.
• Proficiency in at least one modern programming language (Python, R, or Matlab preferred).
• Strong oral and written communication skills.

Nice to have

• Experience in analyzing data from emerging technologies.
• Familiarity with bioinformatic analyses, including scRNA-seq, immune BCR/TCR sequencing, and WGS.
• Background in machine learning or biology.
• Knowledge of cancer genomics.

Culture & Benefits

• Interdisciplinary group of scientists, engineers, and clinicians in a supportive environment.
• Mentoring for postdoctoral trainees to achieve career goals.
• Frequent educational and skill-building opportunities.
• Integration of computational and wet-lab work.
• Comprehensive total rewards package including medical, dental, vision, life, and disability insurance; a 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; and an employee assistance program, among other Broad benefits.