Project # 181
Center name: Biodesign Center for Fundamental and Applied Microbiomics
Campus/Location: Tempe
Faculty lead: Qiyun Zhu
Project description
Dr. Qiyun Zhu is leading a DOE-funded project to enhance scikit-bio (https://scikit.bio/), a renowned open-source Python library for bioinformatics. Scikit-bio offers a range of algorithms and data structures extensively utilized in biological data analysis. Our goal is to augment its capabilities, particularly in handling and interpreting large-scale, multi-layered biological data (multi-omics), crucial for unraveling the intricate interactions among organisms and the environment. Specifically, we seek to recruite 1-3 students to add and refine functionalities for 1) efficient processing of diverse data types, 2) seamless integration of multi-omic datasets, and 3) characterization and labeling (annotation) of biological elements. This opportunity is a gateway for students to collaborate with leading bioinformatics experts and software engineers. Ideal candidates should have a keen interest in open-source scientific computing and a basic understanding of programming, preferably in Python. Students from diverse academic backgrounds who are enthusiastic about merging computing with biology are encouraged to apply. Participants will receive hands-on experience in contributing to high-quality software, valuable mentorship, and skill development that is highly desired in both academic and industry settings. This experience will be a significant stepping stone in your career in bioinformatics, software development, or data science.
Special skills needed
* Strong programming skills, preferably in Python, is essential for this position.
* Experience in open-source software development is highly preferable but not essential.
* Experience or interest in machine learning, computer science, mathematics, or statistics is preferrable but not essential.
* Experience or interest in evolutionary biology, ecology, genetics, molecular biology, or any other biology fields is preferrable but not essential.
* The applicant may read the scikit-bio guideline for contribution: https://scikit.bio/contribute.html to assess their comfortableness with the development work.Any major is appropriate, as long as you have the right skillset. Some successful candidates were from majors such as Computer Science, Biomedical Engineering, Biotechnology, Mathematics, Statistics, etc.
Majors
Any major is appropriate, as long as you have the right skillset. Some successful candidates were from majors such as Computer Science, Biomedical Engineering, Biotechnology, Mathematics, Statistics, etc.
Years
-First Year Students (new to ASU Fall 2025)
-2nd Year Students
-3rd Year Students
-4th Year Students- Seniors
-ASU Online Barrett Honors Students (fully remote work)
Themes
Cross-listed with the following themes:
Biological, Chemical, and Physical Sciences, Data Analytics and Mathematics, Health and Wellness