About the Internship

We are looking for a motivated intern in AI & Computational Biology to support the development and application of machine learning methods on large-scale biological datasets. This role is ideal for students or recent graduates in computational biology, bioinformatics, AI/ML, or data science who are passionate about applying their skills to real-world biomedical problems.

As part of the Computational Biology team, you’ll work alongside experienced scientists and engineers, gaining hands-on experience with high-dimensional omics data and the opportunity to contribute to projects that impact drug discovery in oncology.

What You’ll Do

• Support development of ML models for biological data analysis, with guidance from senior team members.

• Process and integrate multi-modal datasets such as transcriptomics, genomics, and phenotypic screens from PDOs.

• Contribute to exploratory data analysis, visualization, and preprocessing pipelines to uncover patterns and validate hypotheses.

• Assist in prototype implementations of generative and predictive models under supervision.

• Participate in weekly team meetings and project updates, contributing ideas and presenting your findings.

Must Have skills

• A student or recent graduate in computational biology, bioinformatics, machine learning, data science, or related fields.

• Curious about cancer biology and excited by the idea of translating data into real therapeutic impact.

• A strong team player who is proactive, detail-oriented, and thrives in a collaborative and fast-paced research environment.

• Very comfortable with coding in Python.

• Familiar with machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow) and have a strong understanding of ML fundamentals.

Nice to Have skills

• Exposure to RNA-seq or other omics data and tools like scanpy, anndata, or Bioconductor packages.

• Familiarity with deep learning or generative models.

• Interest in oncology, organoids, or translational research.