We seek an outstanding researcher for a project addressing randomised algebra algorithms for real-time process analytics. In essence, the aim is to develop statistical computing tools that utilise a priori available information on model structure. This project is funded by EPSRC, and will be based at the School of Engineering of the University of Edinburgh. The successful applicant will conduct research into developing and analysing randomised sampling algorithms for solving partial differential equations on high dimensional models and inverse regression problems to estimate model parameters. The responsibilities include the design of randomisation algorithms for finite element matrix sketching, design of subset selection algorithms for large-scale regression, analysis of the randomisation-induced error to quantify the variance in the estimated quantities, software implementation in Matlab or Python, and publishing peer reviewed articles and presenting work at conferences.
The post is funded for 24 months, starting March 1st, 2018.
The successful candidate will implement lnfra-Red Chemical Species Tomography (CST) systems on a variety of combustion plant, such as marine engines and gas turbines, and will explore process engineering applications of electrical tomography. They will have in-depth knowledge of tomographic measurement systems and image reconstruction methods, and will be able to adapt optical, mechanical, and both analogue and digital electronic sub-systems, to new target processes. The Edinburgh group in Agile Tomography sits within the Research Institute for Digital Communications. The ability to liaise productively with a range of academic and industrial partners is essential.
The University of Edinburgh is one of the world’s top 25 institutions of Higher Education and provides exceptional research, teaching, and living environments. The School of Engineering reflects the University’s principal characteristics, with a cosmopolitan academic staff numbering over 125, and with a body of ca.