ProFound Therapeutics: Bioinformatics Data Engineering Co-Op
About the role
This position is open exclusively to current Northeastern University Co-Op students.
Location: Watertown, MA
Work Period: January 2027 to June 2027. This is a full - time, 40 hours per week position with hybrid schedule.
About ProFound Therapeutics
ProFound™ Therapeutics is a biotechnology company discovering novel proteins across the expanded human proteome to unlock first-in-class medicines and transformative drug targets. The company’s proprietary ProFoundry™ Platform integrates state-of-the-art protein detection, validation, and computational technologies to systematically identify and characterize previously inaccessible proteins and validate their therapeutic potential. This approach has generated a rapidly expanding portfolio of novel targets and drug discovery programs advancing toward the clinic, enabled by strategic collaborations with leading pharmaceutical partners. Together, these efforts support the development of breakthrough treatments across a broad range of disease areas.
The company is now poised to define the disease-relevant function of these proteins at scale using advanced proteomics technologies, high throughput experimental biology, and causal agentic AI, enabling rapid identification and characterization of the most promising protein drugs and drug targets.
Founded by Flagship Pioneering, ProFound works with pharmaceutical partners including Novartis, Pfizer and GSK, and with the Gates Foundation, which has committed up to $35 million to a ProFoundprogram focused on preeclampsia.
About Flagship Pioneering
ProFound Therapeutics was founded by Flagship Pioneering's venture creation engine that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the company’s Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.
Flagship Pioneering Co-Op Program
Welcome to Flagship Pioneering Co-Op Program for the cohort dreaming big and taking courageous leaps. You'll join fellow peers across our ecosystem of companies and learning firsthand how we build first-in-category companies. You’ll have access to enrichment sessions, a dedicated professional development track, and a mentor that help guide you toward your next step. By the end, you will carry on a meaningful project outcome, a genuine network, and a front-row view of how Flagship pioneer new ventures that change the world.
Position Summary
As a Bioinformatics Data Engineering Co-Op, you’ll work on production pipelines and datasets, with code review and mentorship from the team. You’ll own a scoped project from start to finish and present it to the team at the end. Typical projects include a QC dashboard, a pipeline benchmark, a new annotation resource or a statistics module. You’ll also work directly with the scientists who use what you build.
The Co-Op is designed to complement your academic training with hands-on experience in production bioinformatics and data engineering in an industry drug discovery setting.
Key Responsibilities
Responsibilities include, but are not limited to, the following.
- Run and monitor pipelines. Run Nextflow pipelines for ribosome profiling (Ribo-seq), long-read sequencing and DIA proteomics on AWS Batch. Triage failed jobs and summarize QC with MultiQC and alignment metrics.
- Build and validate QC. Flag samples that fail set thresholds. Compare results across GENCODE versions. Write automated checks that catch suspicious or missing experiment data before it reaches downstream scoring.
- Analyze proteomics evidence. This includes peptide-to-protein mapping, sequence coverage, FDR-filtered evidence, and comparisons across search engines and experiments.
- Write and test scripts. Use Python and R to parse, filter and summarize outputs (FASTA, GTF, BAM, peptide and protein tables) into Parquet or TSV. Turn exploratory notebooks into reusable, version-controlled code.
- Grow the data catalog. Add or update a dataset: ingest it, document its schema and check it with Athena (SQL) queries.
- Build tools for scientists. Prototype a visualization or dashboard (Plotly/Dash, Streamlit or a notebook) that scientists use to review targets and QC results.
- Document and share. Write READMEs and runbooks, and present results in team meetings, including a final co-op presentation.
Example Projects
- Benchmark two MS search engines on the same dataset and report where they agree and where they disagree.
- Build a Ribo-seq QC report that flags samples failing periodicity or mapping thresholds.
- Add a new QC view to a scientist-facing dashboard, from requirements through deployment.
- Ingest and document a new biological annotation resource in the data catalog.
Qualifications
Required
- Currently pursuing a B.S. or M.S. in Bioinformatics, Computational Biology, Biology, Biochemistry, Computer Science or a related field, and available for a full-time, 4–6 month co-op term.
- Python (pandas) and comfort with the Linux command line.
- Git, and a habit of writing clear, tested, reproducible code.
- Coursework or project experience in genomics or molecular biology, such as RNA-seq, translation, protein or DNA sequence analysis, or proteomics basics.
- Clear written communication; you document what you build.
Preferred
- Basic R.
- SQL.
- Nextflow, Snakemake, Airflow or another workflow manager, plus Docker.
- Exposure to AWS (e.g., S3, EC2, Athena).
- Familiarity with Ribo-seq, long-read sequencing or mass spectrometry data (e.g., peptides, PSMs, database search).
- Basic statistics, such as differential expression, false discovery rate and multiple-testing correction.
- A dashboard or web app you’ve built (e.g., Dash, Streamlit, Shiny), linked from GitHub or a portfolio.
- Experience with AI coding assistants (e.g., Claude Code, Copilot, Cursor) on real projects, with a sense of where they help and where they fail.
- Exposure to LLM APIs, agents, MCP, or classic ML (e.g., scikit-learn, PyTorch) applied to biological data.
What You’ll Learn and Gain
- How production Nextflow pipelines are built, tested and run on the cloud.
- How a data catalog (Glue, Athena, Parquet) turns raw omics outputs into queryable resources.
- How a computational team supports a drug discovery platform, with exposure to the wet-lab work behind the data.
- How to use AI-assisted development responsibly in a regulated, data-sensitive setting: verification, testing, and knowing what data may and may not go to which tools.
- A shipped project with your name on it.
What We Offer
- Build alongside founders. You’ll work inside the same hypothesis-driven process Flagship uses to conceive and launch first-in-category companies.
- This can be the start of a longer story. Strong co-ops are considered for future opportunities across Flagship and its portfolio companies, not just for this one role.
- Work alongside people who left the safe path. Your colleagues are scientists, engineers, and operators who chose to build something new rather than join something already established.
- Take on real ownership. You're contributing to ventures that are still being defined. Your work can shape real decisions, not just support them.
- Be paid like the contributor you are. Compensation reflects the real work you take on.
Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
The pay range for this role is $25 - $35 per hour. This role is a short-term engagement that is not eligible for health and welfare benefits. Retirement benefits may be available after completing a set number of hours. Compensation and benefits information is based on ProFound's good faith estimate as of the date of publication and may be modified in the future.
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