Our Computational Biology team builds prediction and optimization tools for payload design and manufacturing in cell and gene therapy. We analyze multi-omic datasets—particularly single-cell RNA/DNA—to improve drug design and power WLG’s in-silico tools, pipelines, and models.

As a Computational Biology Intern, you will work directly with the whole Computational Biology Team and you’ll be mentored by our Head of Computational Biology. Throughout your internship, you will gain hands-on experience in epigenomic and transcriptomics analysis as well as machine learning and you will contribute to the development of multi-omics analysis pipelines as well as promoter design models. You’ll have the opportunity to help drive WhiteLab Genomics forward by assisting in the development of innovative solutions. At the end of your 6-month internship, you’ll present your findings and insights to all WhiteLab Genomics teams, showcasing the impactful work you’ve done and the skills you’ve developed during your time with us.

Here’s How You’ll Make an Impact…

• You will develop methods leveraging multi-omic data to optimize synthetic DNA sequence design for cell & gene therapy.

• You will run and improve bioinformatics analyses (with a focus on single-cell, transcriptomics, and epigenomics).

• You will help design, implement, and validate machine learning approaches for synthetic promoter design and related models.

• You will collaborate in cross-functional projects with project managers, scientists, and engineers.

• You will communicate results clearly (notes, dashboards, presentations) and present your work company-wide at the end of the internship.

We’re Eager to Meet You If…

• You have a master’s in bioinformatics, biostatistics, Computational Biology or a related field

• You have comprehensive programming skills in Python or R with experience in bioinformatics toolkits and libraries (e.g. Bioconductor, scikit-learn)

• You possess comprehensive communication skills, curiosity, and have a proactive can-do attitude

• You’re proficient in English and you’re eager to dive into a multicultural workplace, where both English and French are spoken regularly

• You have knowledge of molecular biology principles

• You are familiar with biological databases and resources

• You are familiar with statistical approaches for biological data analysis, especially single-cell RNA-seq

• Intro video call (30 min) with People & Culture

• Technical interview (45–60 min) with the Head of Computational Biology

• Onsite loop (2–3 hrs) with the Computational Biology team

• Reference checks → Offer