Department of Automatic Control and Systems Engineering

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Department of Automatic Control and Systems Engineering

Faculty of Engineering

Automatic Control and Systems Engineering (ACSE) is the largest department devoted to systems and control engineering in the UK and amongst the largest in Europe. It comprises 24 academic staff, 29 research staff, 24 support staff and over 350 undergraduate and postgraduate students. We are an internationally leading research department and have a vibrant research culture spanning systems and control theory and its increasingly challenging applications in, for example, medicine, aerospace and manufacturing systems, to the increasingly important aspect of the complex systems challenges of the coming decades: systems/synthetic biology, neuroscience and cognition, healthcare, smart materials and sensors, autonomous systems, transport, energy and the environment, and space science. We approach these challenges by a focus on the generic theoretical developments in complex systems analysis, modelling, control and computational intelligence that underpin strategic, multi-disciplinary collaborations with leading groups in application areas.

The post holder will work within a team funded by SELEX ES seeking to develop sequential Monte Carlo methods for solving problems such as group object tracking and distributed inference in sensor networks.

The project will seek to develop scalable Bayesian approaches able to solve complex and high dimensional problems with multi-sensor data. One such problem is tracking groups and extended objects. For single object tracking there are well established models but modelling the motion of a group of objects is an unresolved challenge.

Amongst the problems that will be studied are: modelling the interactions within group components, for example, within a group of people (such as from video data), or a convoy of vehicles moving in urban environment, and followed by the development of techniques for tracking the motion and the structure of the group based on data coming from a network of sensors (e.g. with radar and LIDAR data).

The project will also involve the investigation of extended object tracking, sensor fusion techniques to detect, identify and track formations (collectives) of targets and providing predictions of future formation behaviour in complex sensor environments and their efficient implementation.

Main Duties and Responsibilities

Plan and undertake the research and development necessary to achieve the aims of the project.
Contribute to the writing of research reports, progress reports, presentations and any other reporting obligations.
Disseminate the results via journals, conference presentations, and project meetings.
Maintain accurate and complete records of all findings.
Develop his/her scientific background, specialist knowledge and scientific contacts.
Participate in project meetings.
Attend national and international conferences and workshops to present the research results to a wider audience and stay up to date with current advances in the field.
Collaborate with the project partners from University of Cambridge, QinetiQ and other project partners.
Any other duties, commensurate with the grade of the post.

Applicants should provide evidence in their applications that they meet the following criteria. We will use a range of selection methods to measure candidates’ abilities in these areas including reviewing your on-line application, seeking references, inviting shortlisted candidates to interview and other forms of assessment action relevant to the post.

Criteria / Essential / Desirable
Qualifications and experience
1. / Hold, or be close to completing, a PhD degree in signal processing, electrical engineering, aerospace engineering, mathematics, statistics, physics, or a related area. / X
2. / Thorough knowledge of Monte Carlo estimation techniques and object tracking sensor fusion techniques in order to detect, identify and track formations. / X
3. / Strong background in experimental research. / X
4. / Evidence of software and hardware development skills. / X
Communication skills
5. / Effective communication skills, both written and verbal, report writing skills and experience of delivering presentations. / X
Team working
6. / Evidence of working collaboratively within a research team. / X
Problem solving and decision making
7. / Ability to develop creative approaches to problem solving. / X
8. / Ability to analyse and solve problems with an appreciation of longer-term implications. / X
Project management
9. / Experience of a range of project management approaches. / X
Personal effectiveness
10. / Experience of adapting own skills to new circumstances. / X
11. / Ability to work independently on a research task whilst adhering to deadlines and achieving project milestones. / X
12. / Willingness and ability to exploit opportunities arising from the research. / X

This post is fixed-term with a start date of 1 November 2013 and an end date of 31 May 2014.

Terms and conditions of employment: Will be those for Grade 6 staff.

Salary for this grade:£24,289 to £28,132 per annum.

More details on salaries, terms and conditions and our wide range of benefits for staff are available at

Closing date: TO BE CONFIRMED BY HR

Informal enquiries:

For all on-line application system queries and support, contact: .

For informal enquiries about this job and department, contact: Dr Lyudmila Mihaylova at

Following the closing date, you will be informed by email whether or not you have been shortlisted to be invited to participate in the next stage of the selection process. Please note that due to the large number of applications that we receive, it may take up to two working weeksfollowing the closing date before the recruiting department will be able to contact you.

It is anticipated that interviews and other selection action will be held on XXX. Full details will be provided to invited candidates.

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