partial rankings and aggregate ranks

When interviewing impressive applicants from a stunning variety of places and background for fellows in our Data Science for Social Good program (in Warwick and Kaiserslautern) this summer, we came through the common conundrum of comparing ranks while each of us only meeting a subset of the candidates. Over a free morning, I briefly thought of the problem (while swimming) and then wrote a short R code to infer about an aggregate ranking, ρ, based on a simple model, namely a Poisson distribution on the distance between an individual’s ranking and the aggregate

a uniform distribution on the missing ranks as well as on the aggregate, and a non-informative prior on λ. Leading to a three step Gibbs sampler for the completion and the simulation of ρ and λ.

I am aware that the problem has been tackled in many different ways, including Bayesian ones (as in Deng et al., 2014) and local ones, but this was a fun exercise. Albeit we did not use any model in the end!

Data science for social good fellowships [DSSGx UK 2023]

Warwick is (again) running a 12-week summer programme bringing together some of the top student talents from data science, machine learning and artificial intelligence, all over the World, to work on real-world data science challenges and deliver positive social impact. Applications for DSSG 2023 are now OPEN! Click here for the application form (please read the information carefully) and click here for the FAQs for 2023. (The application also works for a similar programme in Kaiserslauten, Germany.

DSSG helps not-for-profit organisations and government bodies to achieve more with their data by enhancing their services, interventions and outreach, helping fulfil their mission of improving the world and people’s lives.

The programme gives not-for-profit organisations and government bodies unprecedented access to inspiring, top-tier data science talent. This helps build their capacity to use cutting-edge quantitative methods to address societal challenges in areas such as education, health, energy, public safety, transportation and economic development.

At the same time, it provides intensive case-based and supported training to students to create industry-standard data science products in collaboration with government agencies and NGOs, to deliver positive social impact. And it builds a world-wide community of data scientists who care about the social good.

In 2019, the University of Warwick together with the Alan Turing Institute brought DSSG to the UK. The University of Warwick has run it each year since and now preparation is well underway for DSSGx UK 2023, which will be held at the University of Warwick, UK, from 5 June to 25 August.

data assimilation and reduced modelling for high-D problems [CIRM]

Next summer, from 19 July till 27 August, there will be a six week program at CIRM on the above theme, bringing together scientists from both the academic and industrial communities. The program includes a one-week summer school followed by 5 weeks of research sessions on projects proposed by academic and industrial partners.

Confirmed speakers of the summer school (Jul 19-23) are:

• Albert Cohen (Sorbonne University)
• Masoumeh Dashti (University of Sussex)
• Eric Moulines (Ecole Polytechnique)
• Anthony Nouy (Ecole Centrale de Nantes)
• Claudia Schillings (Mannheim University)

Junior participants may apply for fellowships to cover part or the whole stay. Registration and application to fellowships will be open soon.

Xmas tree at UCL, with a special gift

Ph.D. students at UCL Statistics have made this Xmas tree out of bound and unbound volumes of statistics journals, not too hard to spot (especially the Current Indexes which I abandoned when I left my INSEE office a few years ago). An invisible present under the tree is the opening of several positions, namely two permanent lectureships and two three-year research fellowships, all in Statistics or Applied Probability, with the fellowship deadline being the 1st of December 2019!

Florence Nightingale Bicentennial Fellowship and Tutor in Statistics and Probability in Oxford [call]

Reposted: The Department of Statistics is recruiting a Florence Nightingale Bicentennial Fellowship and Tutor in Statistics and Probability with effect from October 2019 or as soon as possible thereafter. The post holder will join the dynamic and collaborative Department of Statistics. The Department carries out world-leading research in applied statistics fields including statistical and population genetics and bioinformatics, as well as core theoretical statistics, computational statistics, machine learning and probability. This is an exciting time for the Department, which relocated to new premises on St Giles’ in the heart of the University of Oxford in 2015. Our newly-renovated building provides state-of-the-art teaching facilities and modern space to facilitate collaboration and integration, creating a highly visible centre for Statistics in Oxford. The successful candidate will hold a doctorate in the field of Statistics, Mathematics or a related subject. They will be an outstanding individual who has the potential to become a leader in their field. The post holder will have the skills and enthusiasm to teach at undergraduate and graduate level, within the Department of Statistics, and to supervise student projects. They will carry out and publish original research within their area of specialisation. We particularly encourage candidates working in areas that link with existing research groups in the department to apply. The deadline for application is September 30, 2019.

If you would like to discuss this post and find out more about joining the academic community in Oxford, please contact Professor Judith Rousseau or Professor Yee Whye Teh. All enquiries will be treated in strict confidence and will not form part of the selection decision.