Lead Computational Scientist – Spatial Multi-Omics (Postdoc)

Broad Institute of MIT and Harvard; Cambridge (MA); On-site; USD 70,000 - 93,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Retirement plan (401k)

Paid holidays

Parental leave

Employee assistance program

Job summary

Broad Institute of MIT and Harvard is seeking a highly motivated computational biologist to lead spatial multiomics data analyses in collaboration with the Getz Lab at Broad and MGH. The role emphasizes developing novel spatial-genomic methods and explaining findings to clinicians and researchers.

Strong programming, ML, and statistical skills are essential for advancing cancer genomics research in a fast-paced environment.

Qualifications

• PhD in a quantitative discipline such as Bioinformatics, CS, ML, Engineering, Mathematics, Statistics, Physics.
• 0-1+ years of post-graduate experience.

Responsibilities

• Lead data analysis strategies for spatial multiomics data.
• Drive the project’s scientific vision and computational strategies.
• Develop tools for analyzing novel data types.
• Develop spatial/genomic methods to predict tumor outcomes and subtypes.
• Design, implement and test statistical models; analyze experiments.
• Present results to diverse audiences including non-computational researchers.
• Prepare manuscripts, grants, and patents; deliver presentations.
• Mentor junior team members and foster collaboration.

Skills

Python

R

Machine Learning

Statistics

Computational analysis

Team collaboration

Communication

Education

PhD in Bioinformatics/CS/ML/Engineering/Math/Stats/Physics

Tools

Git

Jupyter

Matlab

Job description

Broad Institute of MIT and Harvard is seeking a highly motivated computational biologist to lead spatial multiomics data analyses in collaboration with the Getz Lab at Broad and MGH. The role emphasizes developing novel spatial-genomic methods and explaining findings to clinicians and researchers.

Strong programming, ML, and statistical skills are essential for advancing cancer genomics research in a fast-paced environment.