Genomics Data Science

Your Course
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.

Entry requirements

Minimum 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).

Subjects taught

The programme is structured in three academic semesters (12 calendar months).

The first semester covers Science & Technologies modules that include analytical assignments, laboratory and group work, and a foundation module on Research Methods. Also in the first semester, students will be required to identify and develop the scope for their major research project, which will be further developed and completed in the second and final semesters. The second semester focuses on energy projects and markets analyses interfacing with innovation and Technologies transfer concepts. A major individual Research Project is completed in third semester.

During the last semester of this programme, students will be required to complete their MSc Thesis. Co-requisite for embarking on the Research Project module include, successful completion of the On-line Research Skills (5 credits), and completion of a series of Term Papers related to specific taught modules.

A primary requirement in the MSc Research Project is that the final thesis should be of near publishable quality for peer-reviewed journals in the relevant Sustainable Energy and Green Technologies project domain.

Core
The Bioeconomy; A strategy for sustainable fuel, material and chemical production
BSEN30310
Life Cycle Assessment
BSEN30360
Thesis
BSEN40090
Advanced Air Pollution
BSEN40110
Waste to Energy Processes & Technologies
BSEN40320
Energy Systems Integration
BSEN40350
LCA Applications
BSEN40400
Research and Teaching Methods
BSEN40460
Biorefinery Process & Tech
BSEN40560
Energy Systems & Sustainable Environments
CPSC40330

Credits

90

Duration

1 year full-time.

Fees

MSc Sustainable Energy & Green Technologies (X413) Full Time
EU fee per year - € 8085
nonEU fee per year - € 25600

***Fees are subject to change

Enrolment dates

Next Intake: 2020/2021 September

Post Course Info

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 NUIG-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.

More details
  • Qualification letters

    MSc

  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Daytime

  • Apply to

    Course provider