Data Science Training Program
September 10-September 11, 2026

Natalie Gill

Bioinformatician II

Are you reaching the limits of your laptop? Are you new to working on clusters and high performance computing (HPC)? New to CoreHPC, or migrating from Wynton? This workshop will start with basic definitions for computing in a cluster environment, including types of nodes, partitions, and containers. You’ll learn how to access the cluster, transfer files, submit jobs, and run analyses. By the end of this workshop you should be comfortable with:

Getting around CoreHPC

  • Transferring files to and from CoreHPC
  • Submitting jobs to the SLURM queue system
  • Launching pipelines
  • Finding available software modules and container resources
  • Building and running your own custom containers

Visit the workshop site for more details and materials.

This is an advanced workshop in the Computer Skills series. Prior experience with the Unix Command-line is required.

This workshop series is made possible through the generous support of Gladstone Institutes, UCSF and Gladstone-CIRM SRL.

Details

Dates
September 10, 2026
1:00pm-3:00pm
September 11, 2026
1:00pm-3:00pm
Location
Online

The Gladstone Data Science Training Program was started in 2018 to provide trainees with learning opportunities and hands-on workshops to improve their skills in bioinformatics and computational analysis. This program offers a series of workshops throughout the year to enable trainees to gain new skills and get support with their questions and data.

Diversity, Equity, and Inclusion

At Gladstone, we are committed to providing events and professional development activities that resonate with our community’s diverse members. Our goal is to develop creative programming that encompasses a wide variety of ideas and perspectives to inspire, educate, and engage with everyone within our walls.

We want to effect positive change through our events and activities by providing a platform for discussions on important topics related to increasing diversity and inclusiveness in the sciences.