(#107) Computational Biology/Cancer Genomics
For high school/undergraduate students, SkoolMentor is offering a unique 8 week opportunity to conduct remote research in cancer genomics research with a Bioinformatics PhD student at UC San Diego. The mentor has extensive research experience in cancer biology, and is passionate about gleaning biologically relevant insights hidden in cancer genomics datasets using computational techniques. Specifically, he has experience with applying supervised and unsupervised machine learning on large datasets as well as integrating different data modalities to develop testable scientific hypotheses. He has co-authored several papers in high-impact scientific journals. In addition, the mentor has ample experience guiding high school and college students through research projects and can provide letters of recommendation for college/grad school applications.
The specific topics of research can range from the exciting new field of "mutational signatures" and its applications to the analysis of large-scale genomic aberrations such as structural variants, copy number aberrations, and the exciting new field of extrachromosomal DNA. Students will develop hands-on project experience that involves the key steps of the data science workflow (obtaining data, cleaning and processing data so it can be analyzed, and visualizing the data by creating publication quality figures) using the Python and/or R programming languages. In addition, students will learn how to read and analyze scientific papers and gain extensive domain knowledge in cancer genomics. Projects can be adapted to suit the specific interests of the student.
The mentor can provide excellent opportunities for students to create a poster to be presented at science fairs and scientific conferences. This is a great opportunity for students who are curious, want to contribute to patient-oriented research and wish to learn about cutting-edge tools and methodologies in cancer research. Opportunities such as these are also a great way for students to showcase the passion for STEM and stand out in college applications. Limited seats available. The research will be driven by the students.
The student should have some familiarity with programming in Python and be interested in the analysis of cancer genomic data. Some basic biology background in cancer genomics is desirable but not necessary.
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* Application Fee is non-refundable.