JOB | Postdoctoral research position in Scalable Bayes at Lancaster University

Salary: £33,518 to £38,832
Closing Date: Thursday 02 August 2018
Interview Date: To be confirmed
Reference: https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=A2325

Applications are invited for a post-doctoral research associate to develop scalable Bayesian algorithms for Big Data challenges. This is an exciting opportunity to develop cutting-edge and theoretically-supported scalable Monte Carlo methods which are fit-for-purpose for modelling and analysing complex data structures, including large-scale spatio-temporal and network data. This research is funded by EPSRC under the Innovation Fellowship scheme in close collaboration with industrial stakeholders, PROWLER.io, the Heilbronn Institute for Mathematical Research and the Alan Turing Institute. The agenda for this research is to co-design and implement the next generation of data science tools capable of fitting complex statistical models to data, which can be implemented within a modern-day data science environment (e.g. cloud-based services). As part of this research programme, there is an opportunity to gain real-world data science experience of working with industry through a 3-month secondment at PROWLER.io, while benefiting from working as part of the UK’s leading department for industrially-relevant Statistics and Operational Research.

You should have, or be close to completing, a PhD in Statistics, Machine Learning, or a related discipline. You will work directly with the principal investigator (Dr Christopher Nemeth) to undertake and support the research necessary to achieve the aims within the grant. This will include, for example, publishing in leading statistics and machine learning journals/conference proceedings, presentation of research at workshops and conferences, developing code to implement new statistical methods, and active involvement in project meetings. You will be experienced in one or more of the following areas: Bayesian statistics, computational statistics, statistical machine learning, probabilistic modelling. You will have demonstrated the ability to develop new statistical methodology and produce academic writing of the highest publishable quality is essential. Experience in developing research-level software is desirable but not essential.

This position is available for immediate start and will run for up to 36 months (including a 3-month secondment with PROWLER.io). Interviews will be carried out shortly after the closing date.

Interested candidates are strongly advised to contact Dr Christopher Nemeth (c.nemeth@lancaster.ac.uk) in advance of making an application. Applications from people in all diversity groups are strongly encouraged.