Genomics Data Science
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.
3 GOOD REASONS TO STUDY THIS COURSE
1. Combining elements of statistics, data analytics and computational biology, graduates will have a highly marketable and transferable combination of skills.
2. This course provides excellent training for graduates who wish to pursue a research career either in academia or industry.
3. Class sizes are small and most of the modules are taught in a dedicated computer lab.
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.
The Bioeconomy; A strategy for sustainable fuel, material and chemical production
Life Cycle Assessment
Advanced Air Pollution
Waste to Energy Processes & Technologies
Energy Systems Integration
Research and Teaching Methods
Biorefinery Process & Tech
Energy Systems & Sustainable Environments
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).
WHEN TO APPLY: University of Galway does not set a deadline for receipt of applications (with some exceptions). Offers will be issued on a continuous basis. Candidates are encouraged to apply as early as possible.
1 year full-time.
MSc Sustainable Energy & Green Technologies (X413) Full Time
EU fee per year - € 8085
nonEU fee per year - € 25600
***Fees are subject to change
Next Intake: 2020/2021 September
Post Course Info
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.