Geocomputation - National Centre for Geocomputation - Research
This structured research programme in Geocomputation aims to:
• Build capacity for independent research.
• Enhance advanced specialist knowledge in Geocomputation alongside transferable and generic skills.
• Enable students to disseminate their research.
In addition to the modules associated with this particular course, this structured programme offers postgraduate researchers the opportunity to select from modules taught on the MSc in Geocomputation and professional skills training modules offered by different faculties or modules offered by other Departments which are of particular interest, for example research commercialisation.
Students must take a minimum of 10 credits in taught modules (at least 5 in generic/transferable modules and at least 5 in subject specific/advanced specialist modules) from the Structured PhD programme.
Candidates for research degrees will normally be expected to have at least an upper Second Class Honours degree or a relevant Masters degree. Relevant academic backgrounds include Geography, Computing Science, Surveying, Geomatics, Mathematics and Physics. We recommend that candidates contact the Programme Director in the first instance. Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.
Minimum English language requirements:
IELTS: 6.5 minimum overall score
TOEFL (Paper based test): 585
TOEFL (Internet based test): 95
PTE (Pearson): 62
Maynooth University's TOEFL code is 8850
2 years Full-time, 3 years Part-time
Post Course Info
There is an international shortage of highly skilled researchers able to handle large and complex datasets. Thus far our graduates have continued with research in academic environments but there are opportunities in public and private sector research and development, with environmental concerns and policy organisations: much depends on the substantive area of the thesis topic. This might focus on the innovative collection and processing of new datasets, on visualising complex datasets in multiple dimensions, on machine learning or on algorithms for the spatial analysis of data in a particular application area, for example health and retailing.