Internship 1
Host name: Elham Azizi
School and Department: SEAS; Biomedical Engineering and Computer Science; IICD
Internship title: Machine learning tools for analysis of single-cell perturbation data
Number of interns to be hosted: 1 (one)
Types of support offered:
- Stipend: $14,000 over the duration of the internship
- Access to Columbia University campus services, computational resources, and lab meetings
- Mentorship and supervision by faculty and senior lab members
- Immigration and Visa assistance through Columbia’s International Students and Scholars Office (ISSO)
Internship description
The project aims to identify cellular programs driving metastasis using cell line models of breast cancer. The intern will build and leverage computational methods to integrate transcriptomic datasets from genetic and chemical perturbation screens, analyze perturbation responses, and build new machine learning tools to infer regulatory mechanisms underlying metastatic progression.
Types of support offered
Usual Columbia stipend amounts
Skills required
machine learning, programming in Python, statistics, linear algebra, deep learning