Postdoctoral Data Scientist (spatial-temporal localization using wifi)

The University of Manchester and Purple WiFi are looking to recruit a data scientist to undertake and manage a 33 month Knowledge Transfer Partnership (KTP) project, which has the overall aim of developing the most accurate wifi localisation system commercially available. The successful applicant will have a unique opportunity to apply state-of-the-art machine learning methods to address a cutting edge problem with a high level of commercial applicability. They will be involved in all aspects of project development: designing and carrying experiments to collect the data, analysing the data, modelling it, and using the models to predict the location of objects. They will play a vital role in introducing new computational techniques into the company Purple WiFi LTD to support future feature development. This position is particularly suitable for one who wants to bridge academic and industrial research excellence.
The successful applicant will be part of a collaborative development and knowledge-transfer project between The Machine Learning and Optimisation Research Group at The University of Manchester and Purple WiFi LTD. For information about Knowledge Transfer Partnerships, see https://connect.innovateuk.org/web/ktp. They will be employed by the University of Manchester and receive a competitive UK academic salary, but will be sited at the company. They also receive formal project management training, and will have access to a £5,500 personal and professional development budget.
A suitable applicant will require a recent PhD on a topic with mathematical and computational content and experience creating and analysing models from data. For the full specifications and further details, and to apply, see the advertisement on the University of Manchester website
https://www.jobs.manchester.ac.uk/displayjob.aspx?... and the further details at
https://www.jobs.manchester.ac.uk/candidates/Previ.... You are also encouraged to contact the academic supervisor, Dr Jonathan Shapiro (jonathan.shapiro-AT-manchester.ac.uk) for further questions about technical aspects of the project by email. Please quote the job reference number, E&PS-06720, in the email subject. Successful Candidate must start by 13 February, 2016, although obviously sooner would be better.
Application Deadline: 21 August, 2015