The Center of Excellence (CoE) in Data Science and Bioinformatics at LabCorp Information Technology department applies various data science disciplines (including artificial intelligence, machine learning, graph databases, statistics, bioinformatics, and natural language processing) to our clinical, operational and financial challenges, and creates opportunities to enhance the value of our offerings to our customers. Additionally, it integrates the data sciences and bioinformatics efforts between the LabCorp diagnostics and drug development units and serves as a collaboration platform to foster teamwork and learning throughout the LabCorp IT organization.
The internship program in this CoE provide a unique opportunity for the students to interact with the CoE personnel and get hands-on experience and knowledge of solving real life problems in data sciences and bioinformatics. It also contributes directly to LabCorp research and development efforts to address challenging data science issues and speed up critical production development efforts.
Utilize Deep Learning in Position Specific Modeling in Somatic Mutation Detection for Low Frequency Mutations.
This summer internship will provide opportunities to:
- Learn processing and analyzing large datasets from sequencing high-throughput instrument;
- Learn concepts of deep learning;
- Gain exposure to a practical use of dimensional reduction and feature selection in predictive modeling;
- Have a hands-on experience in machine learning methods using high dimensional data in an unbalance population.
As a Summer Intern you will:
- Survey Deep learning tools available with pros and cons, Bringing one or more public tools in house;
- Educate the team through one or more seminar(s) about the deep learning concept with practical examples (use internal or publicly available datasets) for CNV detections, and modeling the noise during SNV detection.
- Enrolled in a graduate program in computer science, applied math, bioinformatics, or related programs;
- Course work and research activities in Machine Learning;
- Course work and research activities in statistical modeling;
- Experience in programming in R and Python;
- Graduate level knowledge in algorithms;
- Familiarity with Linux operating system.
ScheduleMonday through Friday, 8:00-5:00