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Genomics Data Science (MSc)

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Course Overview
Key Facts
Course Outline
Why Choose This Course?
Course Fees
Find Out More

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 advancements in high-throughput technologies used to sequence DNA have led to an unprecedented increase in the availability and use of genomics data, from fundamental scientific discovery in the life sciences to clinical applications in precision medicine. The analysis of these large, complex datasets requires a new generation of highly trained scientists who possess not only a sound understanding of the underlying biological principles and technologies, but also the necessary quantitative and computational skills. Combining elements of genetics, statistical science, data analytics, machine learning, bioinformatics and computational biology, this exciting new programme will provide graduates with a highly marketable and transferable set of data science skills as well as specialist knowledge of and experience in the application of these skills to the analysis and interpretation of genomics data.

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

Applications and Selections

Applications are made online via the University of Galway Postgraduate Applications System.

Who Teaches this Course

Pilib Ó Broin, PhD

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Requirements and Assessment

Students are formally assessed through a variety of both continuous assessment and end-of-semester written examinations. Continuous assessment include written assignments, programming exercises, genomic analyses, individual and group presentations. Assessment of the research project includes a literature review and manuscript, as well as an oral presentation.

Key Facts

Entry Requirements

Applicants must have achieved a first or strong second class honours degree in a quantitative discipline. Qualifying degrees include, but are not limited to, mathematics, physics, statistics, computer science, and engineering (biomedical or electronic/computer engineering).

Additional Requirements

Recognition of Prior Learning (RPL)

Duration

1 year, full-time

Next start date

September 2024

A Level Grades ()

Average intake

QQI/FET FETAC Entry Routes

Closing Date

Please view the offer rounds website.

NFQ level

Mode of study

ECTS weighting

Award

CAO

Course code

MSC-GDS

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.

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Why Choose This Course?

Career Opportunities

Graduates will be well placed to seek employment in a wide range of industries that employ genomics technologies, including biotechnology and pharmaceutical R&D, as well as clinical healthcare. Graduates will also have the option to pursue PhD research, for example in the University of Galway-led SFI Centre for Research Training in Genomics Data Science (genomicsdatascience.ie). Given the highly transferrable and sought after nature of the data science skills learned, graduates may also choose to enter data analyst or data scientist roles in non-genomics domains.

Who’s Suited to This Course

Learning Outcomes

Transferable Skills Employers Value

Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

€8,640 p.a. (including levy) 2024/25

Fees: Tuition

€8,500 p.a. 2024/25

Fees: Student levy

€140 p.a. 2024/25

Fees: Non EU

€27,000 p.a. (€27,140 including levy) 2024/25

Postgraduate students in receipt of a SUSI grant—please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2024/25). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.

Postgraduate fee breakdown = Tuition (EU or NON EU) + Student levy as outlined above.

Note to non-EU students: learn about the 24-month Stayback Visa here.