Learner Profiles

Undergraduate student: Maya Chen

Maya is a 22-year-old undergraduate student in her final year of a Bioinformatics degree. She’s working on her thesis project, which involves analyzing large genomic datasets.

  • Experience: Limited. Has used R for basic data analysis but has never worked with an HPC system.

  • Goals: Needs to learn how to use the university’s HPC cluster to process her data efficiently.

  • Challenges: Feels overwhelmed by command-line interfaces and is unsure how to structure her analysis for parallel processing.

  • Motivation: Wants to complete her thesis on time with repeatable measurement and produce high-quality results that could lead to publication.

PhD student: Amir Patel

Amir is a 28-year-old PhD student in Atmospheric Sciences, in his third year of study. He regularly uses the department’s HPC system for climate modeling.

  • Experience: Moderate. Comfortable with Linux and basic scripting, but relies heavily on job scripts provided by senior lab members.

  • Goals: Wants to understand the scripts he’s using and generate new scripts specific to their purpose.

  • Challenges: Stuggles to use a workflow automation to generate job scripts.

  • Motivation: Aims to become more independent in his research and potentially contribute improvements to the lab’s computational workflow, as well as working towards a reproducible automatic workflow for publications.

Post-doctoral Researcher: Dr. Sophia Müller

Sophia is a 34-year-old post-doc in Computational Physics. She’s preparing a proposal for a large-scale simulation project that requires significant computing resources.

  • Experience: Advanced. Proficient in several programming languages and experienced with various HPC systems, yet currently creates job scripts from scratch or re-purposes older job scripts.

  • Goals: Needs to conduct a scalability study to justify her request for computing time on a national supercomputing facility.

  • Challenges: While comfortable with coding, she’s less familiar with workflow automatin to generate the data scalability study automatically.

  • Motivation: Wants to secure the computing resources necessary for her project, which could be crucial for her career advancement and future grant applications.