ACS e-Science: The University of Manchester

Course description
e-Science is concerned with the automation of tools for the analysis of data via location-independent computing. There is currently an explosion in the volume of data produced in scientific research, and a corresponding proliferation in the formats and services that supply the data. This pathway integrates different tools for managing and interpreting this data and especially deals with the application of location-independent computing to the analysis of the data. This form of computing is know as cloud or grid computing and has produced demanding and novel challenges in the engineering of distributed systems.
e-Science has a strong application driven focus and at Manchester there has been particular focus on its application in biosciences, physics, astronomy and social science. What unites these areas is that they are exemplars of complex systems, in which modelling and experiment are very critically interlinked. The challenge for computer science is to provide automated tools that can enable scientists apply human intuition to the understanding of these systems in their full complexity rather than as greatly oversimplified models. This is an essential step towards an accurate modelling of processes in the real world, and touches on major issues such as the management of climate change, planning for sustainable growth, personalised medicine and response to crises in the environment and in social systems.
The e-Science pathway is centered around a theme of the same name, e-Science, and combines it with a choice of closely related yet complimentary themes, namely Learning from Data,  Data Management, Concurrency, and Advanced Web Technologies.
Career opportunities
Students following the eScience pathway have all the career options as described for general Advanced Computer Science.
In addition, students following this pathway are well placed for careers in the eScience sector, for example, organisations using eScience, cloud, or grid computing technologies for large scale data analysis and modelling.  This includes companies and research laboratories in biosciences, physics, astronomy, and social sciences.
Entry requirements
Academic entry qualification:
They require a First or Upper Second class honours degree, or the overseas equivalent, in computer science, or in a joint degree with at least 50% computer science content. Applicants with extensive computer science industrial experience and a good honours degree, or its overseas equivalent, may also be considered for admission.
English language requirements:
All students are required to be proficient in spoken and written English. In order to be accepted onto an MSc programme in the School of Computer Science applicants need to provide evidence of having achieved the required level in one of the following english language qualifications:

• IELTS score of 6.5 minimum (writing 6)
• Internet based TOEFL 100 with 24 in writing
• Computer Based TOEFL 250 with 5 in TWE
• Cambridge Proficiency Grade 'C'