Data Science and Bioinformatics Intern

Key Skills

Python Programming, SQL, Molecular biology, Bioinformatics

Job Description

The Data Science and Bioinformatics Intern role offers a unique opportunity to apply cross-disciplinary computational expertise for advancing applied CRISPR research. The opportunity is ideal for a graduate student motivated to help scientists in mapping and exploring the vast natural diversity of CRISPR proteins. In doing so, the intern will learn about specific areas where big data and tailor-made bioinformatics solutions lead to discovering new ways to read and write the code of life. Ultimately, this internship offers a chance to make a meaningful contribution towards developing next-generation diagnostic and therapeutic solutions for the world’s most urgent healthcare needs.

KEY RESPONSIBILITIES

• Prototype integrated bioinformatics solution for identifying novel CRISPR-associated proteins and predicting their biological activity
• Implement prediction-ranking workflow for prioritizing most relevant hypotheses based on the experimental constraints
• Think creatively about additional learning opportunities given the available sequence and activity data
• Communicate proactively with the team about the intermediate findings, challenges, and opportunities for further exploration

REQUIRED QUALIFICATIONS

• Undergraduate degree in Biology, Biotechnology, Bioengineering or another related field
• Currently enrolled in a Ph.D. or masters program in bioinformatics, computational biology, bioengineering, or related field
• Proficiency in Python programming, SQL, and using open source platforms for building bioinformatics pipelines

PREFERRED QUALIFICATIONS

• Passion for prototyping fit-for-purpose bioinformatics solutions towards generating testable hypotheses and maximizing learning from available experimental and bioinformatics data
• Research experience in practical aspects of CRISPR biology, prediction, and characterization of CRISPR associated genes
• Exceptional skills in communication, presentations, data analysis, and interpretation