Data Analyst 2, SRS

MIT


Job Location:

Cambridge, MA - USA

Monthly Salary: Not Disclosed
Posted on: 2 days ago
Vacancies: 1 Vacancy

Job Summary

Posting Description

DATA ANALYST SRS COMPUTATIONAL BIOLOGIST Computer Science and Artificial Intelligence Laboratory (CSAIL)-Computational Biology Group to work at the interface of computational and experimental work to develop new computational methods integrate large-scale genomic and single-cell datasets to understand disease circuitry predict new therapeutic target genes and control elements guide experimental dissection refine biological hypotheses and interpret biological results through computational analyses.

The full job description is availablehere:

Job Requirements

REQUIRED: Bachelors degreein computer science/computer engineering or a related field; a minumum of two years of relevant experience; atrack record of computational biology research; experience working with high-dimensional genomic and statistical genetics data; clear understanding of state-of-the-art machine learning and artificial intelligence methods; comfort with a variety of programming languages and data science pipeline; excellent communication and presentation skills; and ability to work as part of a diverse creative team of scientists. PREFERRED: Extensive software engineering experience; familiarity and willingness to engage with Agentic AI workflows deploy software and integrate with large code bases with agentic LLM capabilities; and Masters in computer science/computer engineering or related engineering field.

This position is a 1-year funded position with potential to renew.

6/22/2026


Required Experience:

IC

Posting DescriptionDATA ANALYST SRS COMPUTATIONAL BIOLOGIST Computer Science and Artificial Intelligence Laboratory (CSAIL)-Computational Biology Group to work at the interface of computational and experimental work to develop new computational methods integrate large-scale genomic and single-cell d...

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The MIT Media Lab is an interdisciplinary research lab that encourages the unconventional mixing and matching of seemingly disparate research areas.

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