Applications are invited for a Senior Postdoctoral Research Associate position on Data mining, Analytics, Privacy Protocols and Machine Learning aspects of Personal and IoT data for the the EPSRC Databox Project (http://www.databoxproject.uk ) and the EPSRC Defense Against Dark Artefacts project (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/R03351X/1 ), ideally with a focus on edge computing, Internet of Things, data mining, data visualization, or designing and implementation of and security and privacy protocols and machine learning algorithms.
Job listing information
Closing date 1 July 2018
Salary £36,800 – £44,220 plus benefits
This is full time fixed term position for 14 months, with high possibility of further extensions.
Duties and responsibilities
Design and building efficient and scalable privacy protocols and machine learning algorithms in conjunction with the Databox system
Designing intuitive data discovery and visualisation apps for IoT/Personal data
Engage with the other team members in design and conduct of experiments assessing the interaction of users with exemplar apps and data
Work on a team including the PI, CoIs, and other PDRAs to design the Databox prototype
A new Report, commissioned by the Horizon Digital Research Institute, looks at the industry and consumer market engagement opportunities of the Databox project. The report looks at market engagement with the Databox concept, as it emerges from a limited number of conversations with project stakeholders, business consultants and industry experts. It seeks to explore its value proposition for individuals, ‘data-rich’ companies and ‘data-poor’ companies.
In 2018 we will showcase a live engagement event and demonstrator of the ‘Future of the Living Room’ with the BBC R&D at FACT in Liverpool as part of the States of play exhibition and at the Western Balkans Culture Summit.
The Databox project will be have its first birthday this November. A lot has happened since last year, especially on the platform and analytics side. Please join us for the Year 1 roundup of the research, prototype, and demos of the Databox project. the event will be in the IET London and will include fun and interactive demos with personal data and IoT devices, in addition to research highlights, panel discussions, and debates around the next steps for the project over the next 2 years.
As part of Mozilla Festival 2017, we are inviting you to join us in Databox Hackathon event as a joint summit hosted under the Mozilla Festival pre-week events and a BBC R&D community event.
Please register here:
The full schedule is available on the Eventbrite page.
Last week, our team showcased our Databox platform at BT Innovation week at Adastral Park, Ipswich, UK. There were nearly 5000 visitors over 5 days at the show.
Over the week, our team talked to a mix of businesses – a couple of banks, healthcare providers, a housing association, IoT developers, BBC, Sky, EPSRC and BT researchers. We presented three use-cases: fraud detection, personalised adverts and health insurance. Many attendees were able to see use-cases for their sectors – typical questions were “how much will it cost?”, “when will it be ready/commercialised?”, “how centralised local datastore model is more secure than distributed”, “what would be the physical form factor of the product if deployed?”, “Does it require dedicated hardware?”, “Can it run in BT’s home hub”, “how data usage would be analysed”.
In addition to this, many industry attendees mentioned concerns around GDPR (EU – General Data Protection Regulation) and could see how Databox can help industries/businesses to address the personal data storage related issues. Most of the discussions were about the overall concept and were around “how would I do this/that” and discussion on new potential applications. Overall, the project got positive feedback and follow-up invitations from the audience.
Databox 0.1.2 has been released. Lots of bugs have been squished, ARM7 and 64 support for Raspberry PI and other ARM devices has been improved and the developer experience has been enhanced using local docker images. This is the best Databox release yet!