About
The
Job.
Department of Automatic Control and Systems
Engineering
Faculty of Engineering
Research Assistant in Bayesian
Tracking and Reasoning over Time
About
The
Job.
Pursue the extraordinary
Overview
About the Department
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.
Job Role
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.
Job Description
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.
Person Specification
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
X
processing, electrical engineering, aerospace engineering,
mathematics, statistics, physics, or a related area.
2.
Thorough knowledge of Monte Carlo estimation techniques and
X
object tracking sensor fusion techniques in order to detect,
identify and track formations.
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
X
writing skills and experience of delivering presentations.
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
X
longer-term implications.
Project management
9.
Experience of a range of project management approaches.
Personal effectiveness
X
10.
Experience of adapting own skills to new circumstances.
X
11.
Ability to work independently on a research task whilst adhering
X
to deadlines and achieving project milestones.
12.
Willingness and ability to exploit opportunities arising from the
X
research.
Further Information
This post is fixed-term with a start date of 1 November 2013 and an end date of 31 May
2014.
Benefits
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 www.sheffield.ac.uk/hr/reward/structures
Closing date: TO BE CONFIRMED BY HR
Informal enquiries:
For all on-line application system queries and support, contact:
e-Recruitment@sheffield.ac.uk .
For informal enquiries about this job and department, contact: Dr Lyudmila Mihaylova at
l.s.mihaylova@sheffield.ac.uk
Selection-Next Step
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
weeks following 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.
The University of Sheffield is committed to achieving excellence through inclusion.
The University of Sheffield is proud to be a Two Ticks employer
www.sheffield.ac.uk/hr/equality/support/twoticks
The University has achieved the Athena SWAN award for Women in Science, Engineering
and Medicine