Researcher in Sensor Data AnalyticsFavourite
|Closes:||Friday, 7th July 2017|
|Published:||Tuesday, 6th June 2017|
|Salary:||£29,301 - £38,183 per year|
|Hours:||37.00 hours per week|
|Contract Type:||Fixed Term|
|Position Type:||Full Time|
|Category:||Further / Higher Education|
This is an opportunity to join a new innovation project FITsense, sponsored by The Data Lab Innovation Centre, working as a Research Fellow in Artificial Intelligence/Data Science . This is a full-time post funded for 12 months.
You'll be an enthusiastic and proactive individual with expertise in digital technologies. You'll have strong programming skills and good software development experience and knowledge of data analytics, sensor systems, artificial intelligence and/or case based reasoning would be an advantage.
FITsense will develop a falls prediction system that analyses sensor data captured by technology-enabled FIT homes, to identify patterns of activity that are linked to increased risk of falling. It will combine research in human activity recognition (HAR), with event driven case-based reasoning (CBR). FITsense is a collaborative project between RGU and a partnership of Albyn Social Housing, Carbon Dynamic and NHS Highland.
You will be part of the Artificial Intelligence Research Group with activity in data/text mining, knowledge modeling, and case based reasoning. Recent research develops decision support and recommender systems for digital health and user engagement.
We would particularly welcome applications from women as they are under-represented in this area of our workforce.
The successful candidate will be appointed at either a Research Grade 6 or 7 subject to PhD qualifications and experience (Research Assistant Salary Grade 6 - £29,301 – 32,004, Research Fellow Salary Grade 7 - £32,958 - £38,183). Salary on first appointment is normally to the bottom of the scale for that grade, although in exceptional circumstances an appointment further up the scale may be considered.
Closing date: 7th July 2017
Start date: 1st September 2017
RESPONSIBLE TO: Professor Susan Craw
RESPONSIBLE FOR: No supervisory responsibility
PURPOSE OF POST: The researcher will contribute to the development, implementation and evaluation of AI methods to achieve the objectives of the FITsense project. FITsense will develop a falls prediction system that analyses sensor data captured by technology-enabled FIT homes to identify patterns of activity that are linked to increased risk of falling.
- Develop and carry out a programme of work aligned with the objectives of the FITsense innovation project
- Contribute to the development, implementation and evaluation of innovative AI technologies to address clearly-defined scientific questions for human activity recognition from sensors and an event driven case-based reasoning alert system.
- Participate actively in the production of FITsense deliverables, technical reports, high-impact research publications, and project outcomes.
- Collaborate with other FITsense researchers at RGU to complete research activities to meet objectives to deadline.
- Act as a responsible FITsense team member, leading where agreed, and develop productive working relationship with other FITsense partners.
- Promote and disseminate the project and its results through presentations at conferences, workshops and other appropriate events.
- Assist in developing proposals that may attract research grants, knowledge exchange funding and/ or studentships from external bodies.
- Undertake any other reasonable duties that may be requested by the FITsense principal investigator.
Qualifications and Professional Memberships: An Honours degree in Computing or related discipline at First or Upper Second Class level.
Knowledge and Experience: Software Systems, Databases, APIs, Strong programming skills.
Occasional work outside normal working hours may be required, as well as occasional visits to FIT home site in Alness for trials and demonstrations, and occasional FITsense project team meetings in Alness/Invergordon/Inverness.
Travel to conferences, workshops and seminars in UK, Europe and worldwide, and travel to meetings and events for future funding bids in UK and Europe may be required.
Qualifications and Professional Memberships: A PhD or Masters degree in Artificial Intelligence or related discipline.
Knowledge and Experience: Artificial Intelligence, Data Analytics, Multi-stream Sensor Data, Case-Based Reasoning, Good research publications.
Behaviour 1: Service Delivery - Experience of exploring and adapting a service to meet customers expectations and also identifying ways of improving standards.
Behaviour 2: Communication - Ability to receive, understand d convey both straightforward information, and information requiring careful explanation, in a clear and accurate manner.
Behaviour 3: Decision Making Processes and Outcomes - Experiences of: using own judgement to make decisions; making collaborative decisions with others to reach conclusions; providing advice or information that will influence the decisions of others.
Behaviour 4: Initiative and Problem Solving - Experience of using initiative and creativity to resolve problems, identifying practical and suitable solutions.
Behaviour 5: Team development - Experience of: providing advice or guidance to new starts; delivering training or instruction to others on specific tasks or activities.