BIOSC 1640 @ Pitt
Throughout your major, you have learned foundational biology, chemistry, and computer science. This is a dry-lab course where you learn practical computational techniques and integrate your knowledge. We will use project-based learning, with routine check-ins and technical skill checks that mimic the work of an academic or private-sector career.
Students work on open scientific questions with faculty sponsors. Every project lives in a public GitHub repository. Final deliverables are assessed on reproducibility.
Students use Git, GitHub, and SLURM-based HPC clusters. Pipelines are written in Python with reproducible environments managed by Pixi. Tagged releases with full documentation are the final deliverable.
We seek collaborations with faculty, postdocs, and industry partners. Good projects are computationally tractable in one semester, have clear deliverables, and are scientifically meaningful. Email Dr. Maldonado <alex.maldonado@pitt.edu> to schedule a meeting.
Past Projects
Student teams have tackled open problems spanning structural biology, cheminformatics, and deep learning; each sponsored by faculty or industry partners. These projects produced reproducible pipelines, not term papers.