PhD in Network analysis, Algorithms, Mobile and Sensor computing

This page is for PhD applicants looking to work with Dr. Rik Sarkar

Admissions are open for starting in 2016. See below for various topics and PhD positions.

Students with a scholarship to start earlier are advised to get in touch immediately.

Students from commonwealth countries can consider applying for the
commonwealth scholarship.


The following are some sample research areas, and are all mutually related. You are welcome to work on any combinations of them.

Social & technological networks

Many large datasets are either networks or closely related to networks. For example, social networks, professional networks, biological networks, the internet etc. And we can ask many types of questions in them:

We aim to develop better understanding of networks and fast algorithms to analyze networks and events in networks.

Sensor networks and mobile phones: Context, location and others

Our goal is to use the location technologies and sensors to detect the circumstances and behavior of users to optimize services:

Data mining on low power phones and sensors is challenging, and hence an intriguing research area.

Distributed Computing

Large datasets -- "Big Data" -- cannot be analyzed using a regular computer. They must be processed using many computers in "clusters" or "data centaers." However, many traditional methods of optimization, data mining and learning assume computations on a single computer. Thus:

Computational geometry and topology

Many types of data are "geometric" if viewed in the right way. Computational geometry and toplogy are about finding properties of locations and other coordinate systems to identify the most important characteristics of data. This applies to mobile systems, sensor networks, big data and complex networks. We are interested in:


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.


Students either with or without masters degrees are welocme to get in touch.

The Univeristy of Edinburgh hosts multiple CDTs covering most aspects of computer science. The CDTs provide 4 years of support. You can work with me in either:

    For students interested in big data issues like data mining, analysis etc:

    EPSRC Center for Doctoral Training on Data Science

    For students Interested in Systems:

    EPSRC Center for Doctoral Training on Pervasive Parallelism

    For students in interested in theory, algorithms, geometry etc, both the CDTs above are relevant.

In addition, you can also choose to do a regular Ph.D. outside of CDTs.

If you are not sure which option is best for you, please contact me. In fact, you should contact me anyway before applying. See below.

To apply,

  1. 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.

  2. When instructed to do so, submit formal application at: The PhD application page for Informatics, U. Edinburgh. You can choose to apply to the laboratory for foundations of computer science or to a CDT.

  3. For international students, the deadline for the second step is around December 12, 2015. So please start your process early. Other students are also encouraged to get in touch sooner rather than later.

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, who must apply for additional scholarships to compelete their funding.

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