New York University

Overview

The Bioinformatics (Online) Master of Science (M.Sc.) program at New York University equips students with advanced computational skills necessary for analyzing biological data, particularly in the fields of genomics and sequence-based research. The program emphasizes the application of data science techniques to address real-world challenges in life sciences. Through a structured online curriculum, students engage with a variety of modules and complete a capstone project to showcase their learning and skills.

What you'll study

Programme Structure

The curriculum consists of core bioinformatics courses, applied quantitative training, and a required capstone project, totaling 30 credits. Students will delve into essential topics, blending required modules with electives to enhance their understanding.

Indicative modules/courses include:

• Algorithms and Data Structures for Bioinformatics
• Proteomics for Bioinformatics
• Bioinformatics: Functional Prediction
• Generation Sequence Analysis for Bioinformatics
• Biology and Biotechnology for Bioinformatics
• Applied Biostatistics
• Machine Learning for Bioinformatics
• Sequence and Pathway Analysis

Capstone project

As a culmination of the program, students must complete a capstone project that demonstrates their ability to apply bioinformatics methods to significant problems. This project typically involves data analysis and computational implementation using popular scientific programming tools like Python, R, and shell scripting, and may relate to research or industry datasets.

Entry requirements

Applicants are generally expected to possess a relevant undergraduate degree and meet specific academic criteria. Additional requirements may include standardized test scores, such as GMAT, alongside other qualifications as specified by the university.

Career prospects

Graduates of the Bioinformatics M.Sc. program are well-prepared for various roles in the biotechnology, pharmaceutical, and research sectors. They may pursue careers as bioinformaticians, computational biologists, data scientists, or research analysts, utilizing their expertise to drive advancements in life sciences and healthcare.