Dan Simpson pointed out to me the still open call for an assistant/associate professor (lecturer/reader) position in mathematical statistics at the University of Bath, Southwest England (Somerset to be exact), with a closing date of April 22, i.e., next week. Beside being located in a lovely town on a beautiful campus, this is certainly “a pretty great place to be an early career researcher” to quote from Dan, with an attractive PhD program. Check this link for details. [And you may notice I wisely abstained from cracking any joke about position in bath…]
Archive for United Kingdom
Richard Everitt organises an afternoon workshop on Bayesian computation in Reading, UK, on April 19, the day before the Estimating Constant workshop in Warwick, following a successful afternoon last year. Here is the programme:
1230-1315 Antonietta Mira, Università della Svizzera italiana 1315-1345 Ingmar Schuster, Université Paris-Dauphine 1345-1415 Francois-Xavier Briol, University of Warwick 1415-1445 Jack Baker, University of Lancaster 1445-1515 Alexander Mihailov, University of Reading 1515-1545 Coffee break 1545-1630 Arnaud Doucet, University of Oxford 1630-1700 Philip Maybank, University of Reading 1700-1730 Elske van der Vaart, University of Reading 1730-1800 Reham Badawy, Aston University 1815-late Pub and food (SCR, UoR campus)
and the general abstract:
The Bayesian approach to statistical inference has seen major successes in the past twenty years, finding application in many areas of science, engineering, finance and elsewhere. The main drivers of these successes were developments in Monte Carlo methods and the wide availability of desktop computers. More recently, the use of standard Monte Carlo methods has become infeasible due the size and complexity of data now available. This has been countered by the development of next-generation Monte Carlo techniques, which are the topic of this meeting.
The meeting takes place in the Nike Lecture Theatre, Agriculture Building [building number 59].
[An opportunity to work with Richard Everitt in Reading, UK, in a postdoc position starting this summer]
It is now possible to retrieve the complete DNA sequence of a bacterial strain relatively quickly and cheaply, and population genetics has been revolutionised in the past ten years through the availability of these data. To gain a deep understanding of sequence data, model-based statistical techniques are required. However, current approaches for performing inference in these models do not scale to whole genome sequence data. The BBSRC project “Understanding recombination through tractable statistical analysis of whole genome sequences” aims to address this issue. A position as Post-Doctoral Research Assistant is available on this project, supervised by Dr Richard Everitt in the Statistics group at the Department of Mathematics & Statistics at the University of Reading.
The deadline for applications is March 31, 2016 (details).
Today I am giving a talk at the 9th International Conference on Computational and Financial Econometrics (CFE 2015), in London. The number of parallel sessions there is astounding, which makes me [now] wonder at the appeal of such a large conference and the pertinence of giving a talk in parallel with so many other talks that I end up talking at the same time as Pierre Pudlo, who is presenting our ABC with random forest paper (in the twin CMStatistics 2015!). While I may sound overly pessimistic, or just peeved from missing the second day of workshops at NIPS!, there is no reason to doubt the quality of the talks, given the list of authors (and friends) there. So I am looking forward to see what I can get from this multipurpose econometrics and statistics conference.
[Verbatim from the Alan Turing Institute webpage]Alan Turing Fellowships
This is a unique opportunity for early career researchers to join The Alan Turing Institute. The Alan Turing Institute is the UK’s new national data science institute, established to bring together world-leading expertise to provide leadership in the emerging field of data science. The Institute has been founded by the universities of Cambridge, Edinburgh, Oxford, UCL and Warwick and EPSRC.
Fellowships are available for 3 years with the potential for an additional 2 years of support following interim review. Fellows will pursue research based at the Institute hub in the British Library, London. Fellowships will be awarded to individual candidates and fellows will be employed by a joint venture partner university (Cambridge, Edinburgh, Oxford, UCL or Warwick).
Key requirements: Successful candidates are expected to have i) a PhD in a data science (or adjacent) subject (or to have submitted their doctorate before taking up the post), ii) an excellent publication record and/or demonstrated excellent research potential such as via preprints, iii) a novel and challenging research agenda that will advance the strategic objectives of the Institute, and iv) leadership potential. Fellowships are open to all qualified applicants regardless of background.
Alan Turing Fellowship applications can be made in all data science research areas. The Institute’s research roadmap is available here. In addition to this open call, there are two specific fellowship programmes:
Fellowships addressing data-centric engineering
The Lloyd’s Register Foundation (LRF) / Alan Turing Institute programme to support data-centric engineering is a 5-year, £10M global programme, delivered through a partnership between LRF and the Alan Turing Institute. This programme will secure high technical standards (for example the next-generation algorithms and analytics) to enhance the safety of life and property around the major infrastructure upon which modern society relies. For further information on data-centric engineering, see LRF’s Foresight Review of Big Data. Applications for Fellowships under this call, which address the aims of the LRF/Turing programme, may also be considered for funding under the data-centric engineering programme. Fellowships awarded under this programme may vary from the conditions given above; for more details contact email@example.com.
Fellowships addressing data analytics and high-performance computing
Intel and the Alan Turing Institute will be supporting additional Fellowships in data analytics and high-performance computing. Applications for Fellowships under this call may also be considered for funding under the joint Intel-Alan Turing Institute programme. Fellowships awarded under this joint programme may vary from the conditions given above; for more details contact firstname.lastname@example.org.
Diversity and equality are promoted in all aspects of the recruitment and career management of our researchers. In keeping with the principles of the Institute, we especially encourage applications from female researchers
[A rather stinky piece in The Guardian today, written by a consultant self-styled Higher Education expert… No further comments needed!]
“The reasons cited for this laggardly response [to innovations] will be familiar to any observer of the university system: an inherently conservative and risk-averse culture in most institutions; sclerotic systems and processes designed for a different world, and a lack of capacity, skills and willingness to change among an ageing academic community. All these are reinforced by perceptions that most proposed innovations are over-hyped and that current ways of operating have plenty of life left in them yet.”