Here are the slides of the presentation I gave at the EPSRC Advanced Computational methods for complex models in Biology at University College London, last week. Introducing random forests as proper summaries for both model choice and parameter estimation (with considerable overlap with earlier slides, obviously!). The other talks of that highly interesting day on computational Biology were mostly about ancestral graphs, using Wright-Fisher diffusions for coalescents, plus a comparison of expectation-propagation and ABC on a genealogy model by Mark Beaumont and the decision theoretic approach to HMM order estimation by Chris Holmes. In addition, it gave me the opportunity to come back to the Department of Statistics at UCL more than twenty years after my previous visit, at a time when my friend Costas Goutis was still there. And to realise it had moved from its historical premises years ago. (I wonder what happened to the two staircases built to reduce frictions between Fisher and Pearson if I remember correctly…)
Archive for EPSRC
I spent [most of] the past week in Oxford in connection with our joint OxWaSP PhD program, which is supported by the EPSRC, and constitutes a joint Centre of Doctoral Training in statistical science focussing on data-intensive environments and large-scale models. The first cohort of a dozen PhD students had started their training last Fall with the first year spent in Oxford, before splitting between Oxford and Warwick to write their thesis. Courses are taught over a two week block, with a two day introduction to the theme (Bayesian Statistics in my case), followed by reading, meetings, daily research talks, mini-projects, and a final day in Warwick including presentations of the mini-projects and a concluding seminar. (involving Jonty Rougier and Robin Ryder, next Friday). This approach by bursts of training periods is quite ambitious in that it requires a lot from the students, both through the lectures and in personal investment, and reminds me somewhat of a similar approach at École Polytechnique where courses are given over fairly short periods. But it is also profitable for highly motivated and selected students in that total immersion into one topic and a large amount of collective work bring them up to speed with a reasonable basis and the option to write their thesis on that topic. Hopefully, I will see some of those students next year in Warwick working on some Bayesian analysis problem!
On a personal basis, I also enjoyed very much my time in Oxford, first for meeting with old friends, albeit too briefly, and second for cycling, as the owner of the great Airbnb place I rented kindly let me use her bike to go around, which allowed me to go around quite freely! Even on a train trip to Reading. As it was a road racing bike, it took me a trip or two to get used to it, especially on the first day when the roads were somewhat icy, but I enjoyed the lightness of it, relative to my lost mountain bike, to the point of considering switching to a road bike for my next bike… I had also some apprehensions with driving at night, which I avoid while in Paris, but got over them until the very last night when I had a very close brush with a car entering from a side road, which either had not seen me or thought I would let it pass. Gave me the opportunity of shouting Oï!
The Statistics Department – University of Oxford and the Statistics Department – University Of Warwick, supported by the EPSRC, will run a joint Centre of Doctoral Training in the theory, methods and applications of Statistical Science for 21st Century data-intensive environments and large-scale models. This is the first centre of its type in the World and will equip its students to work in an area in growing demand both in academia and industry.
Each year from October 2014 OxWaSP will recruit at least 5 students attached to Warwick and at least 5 attached to Oxford. Each student will be funded with a grant for four years of study. Students spend the first year at Oxford developing advanced skills in statistical science. In the first two terms students are given research training through modular courses: Statistical Inference in Complex Models; Multivariate Stochastic Processes; Bayesian Analyses for Complex Structural Information; Machine Learning and Probabilistic Graphical Models; Stochastic Computation for Intractable Inference. In the third term, students carry out two small research projects. At the end of year 1, students begin a three-year research project with a chosen supervisor, five continuing at Oxford and five moving to the University of Warwick.
Training in years 2-4 includes annual retreats, workshops and a research course in machine learning at Amazon (Berlin). There are funded opportunities for students to work with our leading industrial partners and to travel in their third year to an international summer placement in some of the strongest Statistics groups in the USA, Europe and Asia including UC Berkeley, Columbia University, Duke University, the University of Washington in Seattle, ETH Zurich and NUS Singapore.
Applications will be considered in gathered fields with the next deadline of 24 January 2014 (Non-EU applicants should apply by this date to maximise their chance of funding). Interviews for successful applicants who submit by the January deadline will take place at the end of February 2014. There will be a second deadline for applications at the end of February (Warwick) and 14th March (Oxford).
A new EPSRC programme grant, called i-like, has been awarded to researchers in Bristol, Lancaster, Oxford, and Warwick, to conduct research on intractable likelihoods. (I am also associated to this program as a [grateful] collaborator.) This covers several areas of statistics, like big data and inference on stochastic process, but my own primary interest in the programme is of course the possibilities to conduct collaboration on ABC and composite likelihood methods. (Great website design, by the way!)
A first announcement is that there will be a half-day launch in Oxford on January 31, 2013, which program is now available. Followed by a workshop in mid-May in Warwick (to which I will participate). This event is particularly aimed at PhD students and early-career researchers. The second announcement is that the EPSRC programme grant provides funding for five postdoctoral positions over a duration of four years, which is of course stupendous! So if you like i-like as much as I like it, and are a new researcher looking for opportunities in exciting areas, you should definitely consider applying!
On Wednesday, I went to the University of Warwick to take part in a meeting about their new MASDOC programme. This programme was launched last year with the support of the EPSRC in three U.K. universities, Warwick, Lancaster and Cambridge (for math). It prepares graduate (fifth year) students for conducting a PhD in Mathematics or Statistics by providing them with extra tutoring and by creating a “cohort” of students working together on research topics. For the first year, the cohort was made of eleven students selected among applicants from both the UK and abroad. Besides a solid volume of courses in Mathematics, Probability and Statistics, MASDOC has the students working in small teams on an applied math problem (e.g., data assimilation, biomembranes, brain imaging) in order to (a) determine a reserarch programme and (b) propose a solution. The teams switch between (a) and (b) which is a neat good idea. The students are also given a common working room in order to increase their team abilities. When discussing with them, I was quite impressed by their maturity and involvement, as they already had a vision of their research interests. In fact, they have somehow gained one year ahead of the average student in terms of decision-making and planning, if not in terms of contents. Of course, this approach to graduate training is rather elitist in that it cannot be extended to all first-year graduates, however it is a worthy investment by EPSRC and the selected universities for building a core of PhD students and future academics with a broader spectrum, a more mature approach to research and teamwork, and hence a higher efficiency now and later. As a side issue, the MASDOC programme is also pushing for exchanges between institutions at the graduate and PhD levels, which is always a plus. Especially when considering the possibilities offered by the Paris graduate school of mathematical sciences.