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How computer science can help keep you healthy

Well, it has to be good for something...

People sometimes aren't aware just how much computers influence their lives. They've used the internet and mobile phones, seen computer-generated imagery in cinemas, and perhaps realised how much date is being sensed around them. But there are enormous applications for computers in science, arts, and medicine.

Earlier today I did an introductory lecture on using computers to study disease epidemics:

Com­pu­ta­tional epi­demi­ology is the use of math­em­at­ical and com­pu­ta­tional tech­niques to model how dis­eases spread. This is import­ant for answer­ing a num­ber of ques­tions. How infec­tious are dif­fer­ent dis­eases? Why are dif­fer­ent pop­u­la­tions affected dif­fer­ently? How do dif­fer­ent treat­ment regimes work? Is quar­ant­ine effect­ive? We can address these sorts of ques­tions using a range of dif­fer­ent tech­niques, ran­ging from dif­fer­en­tial equa­tions (cal­cu­lus) for simple cases through to com­plex net­works and high-performance sim­u­la­tion for com­plex case — and pos­sibly even mod­el­ling real dis­eases in real-world geo­graph­ies in real time.

This lec­ture is an inter­act­ive intro­duc­tion to these ideas. We’ll explore how dis­eases spread; con­duct an exper­i­ment where we infect each other (kind of); and then see how dif­fer­ent aspects of com­puter sci­ence help us to explore dis­eases and their treatment.

The slides and other material are available here. I've included the slides, and an animation of a simulated epidemic running through a population of people. I've also included an IPython notebook describing some of the mathematics needed and containing all the code I used to generate the graphs and animation from the talk, which might be handy for anyone wanting to explore this area more thoroughly.

PhD studentships in St Andrews

The School of Computer Science has a number of fully-funded PhD scholarships available.

I'd be interested in hearing from anyone interested in working on complex systems, complex networks, sensor networks, or situation recognition. You can find more details about what I'm interested in here. I'm particularly interested in people wanting to cross disciplines somewhat, into applications in environmental science, medicine, or the digital humanities.

The full advertisement is here. Deadline for applications 31 March 2015.

PhD Studentships at University College Cork

There are PhD positions open at University College Cork in the area of video processing.

PhD Studentships at University College Cork in Ireland

Closing Date for Applications: None, positions will remain open until filled. Applications will be reviewed at as soon as they are received.

Project: An Internet Infrastructure for Video Streaming Optimisation (iVID)

The Mobile and Internet Systems Laboratory (MISL) in the Department of Computer Science at UCC is an internationally recognised research centre focused on innovative networking research. iVID is a new research project funded by Science Foundation Ireland to investigate the use of software defined networking (SDN) techniques to optimise the delivery of streaming video. A team of 5 project researchers will work on iVID, including 3 Ph.D. students. The project will involve collaboration with AT&T, EMC and the University of California Riverside.

Applications are invited for fixed-term studentships (annual value of €18K, plus fees) from suitably qualified candidates who wish to undertake a PhD within the Department of Computer Science. Applicants should have a Masters degree in computer science or a closely related discipline, although applications from truly exceptional students with a bachelor's degree will be considered. Ideally, applicants will have some project experience in the areas of video streaming, software defined networks, or more generally network protocols. Applicants must have strong mathematical ability and an interest in systems programming and experimental computer science. Applicants must demonstrate good inter-personal skills, and a high standard of spoken and written English. The positions are open to applicants of any nationality.

How to apply: Applications by email to Mary Noonan and must include "PhD Studentship iVID" in the subject line. Applications must include, in PDF format only:

  1. 1300 word personal statement explaining your interest in the project and networking research;
  2. full CV;
  3. copy of transcript(s) showing names of all courses taken and grades achieved; and
  4. summaries of projects (BSc/MSC), internships and relevant work experience completed.

For more information on MISL and the Department of Computer Science, please see the links below.

Complex networks, complex processes

I'm writing a book on my sabbatical. Or trying to, anyway. So I thought I'd publicise the fact so people can hassle me to keep at it.

I've been working on complex systems for a couple of years, especially on complex networks: things like the way people move through a road and rail network, or how diseases spread through social networks. It's a bit of a change from my previous work on sensor data interpretation, although not as much as you might think: I'm wondering whether we could combine sensing and simulation, to use sensors to confirm predictions or to drive and condition further simulations.

Getting into this area has been -- and is -- a head-wreck. It's both highly mathematical and highly computational. I understand the computing; the maths, not so much. Many computer scientists would have the same reaction, but conversely, so would many mathematicians: the maths would be familiar, the computing a challenge. So effectively in order to make progress you have to climb two learning curves simultaneously: some unusual and challenging mathematics about stochastic processes, simulated using cluster or cloud computing which poses a lot of challenges even for someone used to programming.

This is made harder by the research literature, though, which tends towards sparse mathematical descriptions, which is frustrating at two levels: the computing is probably interesting (to people like me), and it's hard to re-create the results when the computational approach underlying the graphs and results is unclear.

So with this in mind, and because I've never done it before, I've decided to write a textbook: Complex networks, complex processes. (No, I'm not very imaginative when it comes to titles...) The idea is to link the maths to the code, providing everything a research would need to get started with the maths and the computing. Since this is likely to be a book with, shall we say, limited circulation, I've decided not to bother with a publisher and instead make it completely open. You can look at the current state on the web here, download the sources, copy and run the code, or anything needed to get started.

It's a work in progress and it's not very usual to advertise books before they're in a fit state to be read, but I suppose that's just a part of open science: make the process visible, warts and all. It also means I'll hopefully get comments and encouragement to keep at it when it starts to fall by the wayside of other things I have to do. The goal is to get the majority done while I'm on research leave (until September), and comments on style, content, and progress will be most welcome.

Fully-funded PhD scholarship available

I have a fully-funded PhD scholarship available, tenable from September 2015, to work on data science in medicine.

University of St Andrews

School of Computer Science School of Medicine

Funded PhD studentship

The Schools of Computer Science and Medicine are looking to recruit a talented student to work on improving clinical trials of tuberculosis and other conditions using computational techniques.

TB and related conditions are extremely costly in human and financial terms, and trials of new drugs and therapies are complicated by difficult environmental conditions and other factors. Improvements to the trials process will potentially translate directly into improved interventions, and so will help save lives.

We seek to apply data-driven techniques to the design, analysis, and management of such trials. These techniques might include complex networks, computational epidemiology, machine learning, Bayesian analysis, and other cutting-edge approaches to data analytics. The ideal candidate will have an interest in data science applied to medical and biological problems, and an enthusiasm for working as part of a challenging multi-disciplinary project within St Andrews' new Institute for Data-Intensive Research (IDIR).

The studentship will be held jointly between the two Schools, with supervisors from Computer Science (Prof Simon Dobson, Dr Tom Kelsey) and Medicine (Prof Stephen Gillespie, Dr Ruth Bowness).  We offer a stimulating and supportive environment within a small and intimate university in a beautiful setting.

The scholarship is fully funded to cover tuition fees and stipend for a registration period normally expected to be three-and-a-half years.

Informal inquiries can be made in the first instance to Prof Simon Dobson. Applications will be considered until mid-March.