Research Assistant / Associate in Multi-target Tracking and Bayesian Intent Prediction (Fixed Term)

University of Cambridge, Newtown, Cambridge

Research Assistant / Associate in Multi-target Tracking and Bayesian Intent Prediction (Fixed Term)

£33966

University of Cambridge, Newtown, Cambridge

  • Full time
  • Temporary
  • Onsite working

Posted today, 24 Oct | Get your application in now to be one of the first to apply.

Closing date: Closing date not specified

job Ref: d16327378b594a58b15f0edec1b37d9d

Full Job Description

A position exists, for a Research Assistant/Associate in the Department of Engineering to work on developing novel algorithms for multi-target tracking and intent prediction for complex dynamically changing environments, degraded sensor accuracy (for example, due to countermeasures employed by the tracked objects) and evasive targets that undertake manoeuvres to undermine the tracking performance or mask malicious intent. This is part of a project funded by the Defence Science and Technology Laboratory (Dstl) through the MOD WSRF framework.

The post holder will be located in Central Cambridge, Cambridgeshire, UK.

The key responsibilities and duties are to develop and evaluate intent and anomaly detection algorithms for threat detection of sUAS using radar data. This will entail analysing relatively large amounts of recorded data and working closely with Aveillant/THALES and Dstl. Due to the nature of the work, only UK, EU and NATO countries nationals might be considered for this post.

The skills, qualifications and experience required to perform the role are: a) a very good first degree in engineering, computer science or a closely related field and have obtained or be close to obtaining a PhD degree in an area related to Signal Processing or Machine Learning, and b) demonstrable research experience in the areas (one or more) of: tracking, intent prediction, Bayesian inference, radar and sensor data fusion.

It is expected that candidates will have solid programming/modelling experience in an appropriate software tool or programming language, e.g. Matlab/Python/C++.

The successful candidate should exhibit good oral and written communication skills and have experience both of working in a team and managing their own workload. Ability to effectively liaise with Dstl and WSRF industrial partners is highly desirable.

Appointment at Research Associate level is dependent on having a PhD (or equivalent experience). Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.