Computational Science and Engineering Summer Intern – Data Science

Inscripta | Industry | Pleasanton, CA or Boulder, CO | More →

Inscripta was founded in 2015 and recently launched the world’s first benchtop Digital Genome Engineering platform. The company is growing aggressively, investing in its leadership, team, and technology with a recent $150mm financing round led by Fidelity and TRowe price. The company’s advanced CRISPR-based platform, consisting of an instrument, reagents, and software, offers a fully automated workflow that enables multiplexed, trackable editing of cells at an unprecedented scale. Inscripta’s mission is to enable scientists to realize the full potential of biology. Due to rapid growth and recent commercialization, Inscripta has an opening for a Computational Science and Engineering Intern – Data Science located in Pleasanton, CA or Boulder, CO. Remote internships may be possible on a case by case basis.

Summary:
The Department of Computational Sciences and Engineering (CoSE) works collaboratively with multi-disciplinary teams throughout Inscripta. CoSE is responsible for addressing a number of genomic, proteomic, experimental design and other relevant questions by building tools, APIs, pipelines, and incorporating mathematical modeling, machine learning and similar data science approaches. We are a multi-disciplinary team made up of software engineers, data scientists, and bioinformaticians. We are looking for exceptional candidates to spend the summer working at Inscripta on data science projects such as model training, data engineering, and data visualization

Responsibilities:
Internship projects will be tailored to the skills and interests of each intern. Some potential projects are listed below as examples.
• Develop predictive models to improve the performance mammalian genome engineering systems.
• Explore novel deep learning architectures and ensemble learning.
• Build dashboards for data and/or model exploration.

Requirements:
Program Requirements
• Open to M.S., PhD or Bachelor’s students pursuing a degree in computer science, engineering, bioinformatics, biology, biochemistry, physics, statistics, or a related field.
• Must have completed at least 3 years of an undergraduate program to be eligible.
• This internship will last a minimum of 12 weeks throughout the summer and will have full-time hours, 40 hours per week, Monday through Friday.

Minimum Qualifications
• Knowledge of Python, R, or other object-oriented programming language.
• Experience analyzing and extracting insight from high-dimensional datasets.
• Coursework or projects related to machine learning.
• Some software development skills, including a working knowledge of git versioning and branching.
• Ability to communicate clearly about technical aspects of a project in group presentations and written documentation.
• Experience working collaboratively on a team or project.

Desired Qualifications
Projects will vary depending upon the candidate’s background, but experience in one or more of the following skills is desired:
• Experience with DNA/RNA sequencing data analysis.
• Familiarity with modern machine learning methods and models, preferably neural networks.
• Experience training and validating the performance of machine learning models.
• Knowledge of CRISPR biology and/or mammalian genomics.

Inscripta offers a competitive hourly rate for interns. Join us for the summer and work with a great team of people creating cutting edge technology in the world’s first scalable platform for benchtop Digital Genome Engineering. At Inscripta, we don’t just accept difference — we celebrate it, support it, and thrive on it for the benefit of our employees, our innovation, and our community. We are proud to be an equal opportunity workplace because the more inclusive we are as a company, the better our work will be. Inscripta is headquartered in Boulder, CO with offices in Pleasanton and San Diego, CA. This position is located in Pleasanton, CA or Boulder, CO locations. Remote internships may be possible on a case by case basis.