Computational Biology Intern (Boston)

J unior Bioinformatics Student Researcher (Single-Cell Biology)

We are seeking a motivated student with emerging interest in computational biology to join our research group and contribute to single-cell transcriptomics projects. This position is ideal for a student eager to build experience in modern genomics, coding for biological analysis, and collaborative research in a wet-lab + computational environment.

Role Overview

The Junior Bioinformatics Researcher will assist with processing and analyzing single-cell and spatial transcriptomics data, support ongoing projects, and learn standard analysis workflows under mentorship from lab members.

Key Responsibilities

Assist with data parsing, preprocessing and QC of single-cell RNA-seq and spatial transcriptomics datasets

Apply analysis tools such as Seurat, Scanpy, and basic Linux command-line workflows

Support integration, clustering, differential expression, and cell-type annotation

Help maintain organized scripts, notebooks, and data files

Generate visualizations and figures for meetings and data reviews

Participate in lab discussions, contribute ideas, and develop independent skills over time

Training & Skills Development

The student will gain experience in :

R / Python coding for biological data analysis

Single-cell pipelines (10x Genomics, Cell Ranger, Seurat / Scanpy)

Data visualization and reproducible workflows

Basic HPC / terminal use, Git version control, and documentation practices

Biological interpretation of transcriptomic results

Preferred Qualifications

Undergraduate or early grad student in Biology, Bioinformatics, Computer Science, Engineering, Neuroscience, or related field

Interest in learning single-cell genomics and computational analysis

Intermediate experience coding in R or Python (coursework or self-taught accepted)

Curiosity, organization, and willingness to learn new computational tools

Nice-to-Have

Previous coursework in genetics, molecular biology, or data science

Familiarity with Jupyter / RStudio environments