The following are
some sample research areas, and are all mutually related. You are
welcome to work on any combinations of them.
Sensing in mobile phones and networks: Context, location and others
Our goal is to use the
location technologies and sensors to detect the circumstances of a user
for better application performance. Where are the users? What are they
doing? How can we find that and deliver better services and information
to them? These are challenging to do in low power phones and sensors,
and hence an intriguing research area.
Social & complex networks
Many large datasets are either networks or closely related to networks. For example, social networks, professional networks, biological networks, the internet etc. What information can we gain from these networks? Can a social network help us predict which event or movie will be popular? Can we analyze the internet and say how it should be modified for better performance? What are the properties of networks that make them effieicent or inefficient in certain tasks?
Large datasets --
"Big Data" -- cannot be analyzed using a regular computer. They must be
processed using many computers in "clusters" or "data centaers."
However, traditional methods of optimization, data mining and learning
assume computations on a single computer. How can we distribute the
computations to process data on many computers?
Computational geometry and topology
Location is a commonly
available information about people, data and events, and thus
constitute an important attribute in mobile systems, big data and
complex networks. Computational geometry is about making use of
locations and other coordinate systems for better computations in
mobile, distributed or network settings.
Algorithms are the most fundamental elements in computer science. We are intereseted in algorithms relevant
to all the areas above. In the modern age of massive datasets and many
different types of devices, we need algorithms that can operate
rapidly, producing good, but may be not perfect results. Thus we are looking for approximations,
and online, streaming algorithms.
In addition, you can also choose to do a regular Ph.D. outside of CDTs.In all the above, you can apply with or without a masters degree.
Send CV and transcripts to Dr Rik Sarkar by email with subject “PhD in Networks” or “PhD in Algorithms” as appropriate and with an explanation of your interests.
When instructed to do so, submit formal application at: The PhD application page for Informatics, U. Edinburgh. You can choose to apply for one of two Labs: either the laboratory for foundations of computer science or the Institute for Computing Systems Architecture. Or to a CDT.
For the formal application you will need to write a research statement describing your interests, and will have to submit contact information for 2 referees who will be asked for letters of recommendation.
Funding Full funding for 3 years is available for UK and EU students, covering tuition, plus a stipend at the standard EPSRC rate. Partial funding is available for overseas students.
The University of Edinburgh is one of the top 20 in world in the QS rankings. The Edinburgh School of Informatics is the largest in UK and has consistently ranked as the top in research. The historic city of Edinburgh is lively, beautiful, and a great place to live. More information for students are available at here and here