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Research Assistant in Spatio-Temporal Inference for Networked Objects (Part Time, Fixed Term)

Closing date: 
Friday, 15 July 2022

Department of Engineering

A position exists, for a part time (10 hours per week) Research Assistant in the Department of Engineering, to work with Prof. Simon Godsill and his team on the project: "SIGNetS - Signal and Information Gathering for Networked Surveillance".

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

This project aims at developing scalable Bayesian approaches able to solve complex multi-sensor, heterogeneous data problems, aimed at improving localisation, situational awareness and latent intent prediction. The work will develop new approximate inference paradigms based around such techniques as variational inference, Gaussian processes and Monte Carlo to solve problems with many sensors that have limited communication abilities and localised computational resources. Objects to be localised will typically be in coordinated network formations and part of the inference task is to determine the latent connectivities between these objects and to learn their intentionalities. Modelling for individual objects will include investigation of new non-Gaussian Levy process formulations that allow for highly erratic and evasive manoevres and require advanced computational methodologies to infer their behaviour.



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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
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