Genomics Data Science (MSc)

Get the Edge with a Postgraduate Degree from NUI Galway Grainne McNamara - MSc Enterprise Systems Gordan Sands - MSc Medical Physics Biomedical Engineering at NUI Galway Mohammed Hasan – Occupational Health & Safety (MSc)

Course Overview

Rapid advancement in high-throughput DNA sequencing methods has led to an unprecedented increase in the availability and use of genomic data, leading to groundbreaking discoveries in important areas ranging from the life sciences to clinical applications in genomic and precision medicine. The analysis of large and complex datasets generated using these cutting-edge techniques requires a new generation of well-trained scientists, who possess not only the necessary quantitative and computational skills but also a sound understanding of the underlying biological principles.

Combining elements of genetics, statistics, machine learning, data analytics, and computational biology, this exciting programme will provide students with a highly marketable and transferable set of big data science skills, as well as specialist knowledge of and practical experience in the application of these skills to genomic data.

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You may also be interested in one of our other Mathematics, Bioinformatics and Computational Genomics postgraduate programmes.

Key Facts

Entry Requirements

Additional Requirements

Recognition of Prior Learning (RPL)

Course Outline

The course comprises 90 credits; 60 credits are obtained from taught modules that provide both fundamental and advanced training in genomics data science, 30 credits are obtained from an individual research project. During the first semester, students undertake a number of accelerated-format modules covering molecular and cellular biology, probability and statistics for genomics, programming for biology, genomics techniques, medical genomics, and genomics data analysis. Students also take part in a weekly seminar series which introduces them to the latest developments in genomics data science. Early in the semester, students select their research project topic and begin to engage with the associated scientific literature. During the second semester, students take three core modules including further modules in medical genomics and genomics data analysis, as well as a module in genomics research methods. Students also choose three optional modules from a wide selection of topics across the life science, mathematical, and computational disciplines. These options include: applied and advanced immunology, optimisation, data visualisation, Bayesian modelling, bioinformatics, probabilistic models for molecular biology, mathematical molecular biology, and web and network science. During this semester students complete the literature review component of their project. Following semester two exams, students begin the research phase of their MSc where they work full-time on their research project. At the end of this period, each student submits a manuscript based on their research and gives an oral presentation.

Why Choose This Course?

Career Opportunities

Who’s Suited to This Course

Learning Outcomes

Transferable Skills Employers Value

Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

Fees: Tuition

Fees: Student levy

Fees: Non EU

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