PhD/postdoc positions in Network Information-Theoretic Sensor Management

We are looking for candidates with a strong background in statistical signal processing, information theory, and good programming skills in Python and/or Matlab. Doctoral and postdoctoral candidates should have a master’s, and respectively Ph.D., degree preferably in signal processing, mathematics, data-science or related fields with a strong quantitative orientation. 

The successful candidates will develop the underpinning methods and algorithms required for autonomous distributed sensor management and fusion in challenging environments. The project will deliver key advances in intelligent sensing to enable continuous and adaptive surveillance in dynamic environments. Due to the advent of the Internet-of-Things and other extensive sensor networks, algorithms that judiciously manage the communication, sensing, and energy resources of such networks are crucial for efficient inference under various limitation and/or availability constraints for these resources. 

The project will involve the proposal of metrics for quantifying the information perceived by different sensors on multiple stochastic processes. Subsequently, these metrics will guide the development of algorithms for sequentially estimating the state of these processes, fuse information from heterogeneous sensors, and allocate resources based on information-theoretic criteria. These resulting algorithms will be applied to multiple target tracking with sensor networks. Building on recent developments by the investigators in multi-target tracking and distributed sensor fusion, this work programme will develop methods based on point process theory, which is designed to accommodate uncertainty in the states of individual targets and the number of targets. Information-theoretic metrics tailored for point processes will be proposed as well as optimization methods that employ these metrics in order to allocate sensor resources and refine the knowledge of the scene. 

For an informal discussion to find out more about the role please contact Professor Daniel Clark at daniel.clark@soton.ac.uk and Dr Augustin Saucan at Telecom SudParis augustin.saucan@telecom-sudparis.eu.

Doctoral applications should include (i) a curriculum vitae, (ii) a transcript of completed courses and grades (iii) a letter of motivation, and (iv) names and contact details of three referees. Post-doctoral applications should include only elements (i), (iii), and (iv) from the previous list. Candidates should send all application material in a single pdf or zip file to daniel.clark@telecom-sudparis.eu