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Post-Doctoral Research Assistant position "Assessing Spatial Heterogeneity through Random Walks on Graphs"

We invite applications for an experienced Postdoctoral Research Assistant, to

work on the project "Assessing spatial heterogeneity through random walks on

graphs", funded by EPSRC, under the supervision of Dr. Vincenzo Nicosia.

The post is full-time and fixed-term for 12 months, starting on 3 February 2020

or as soon as possible thereafter. Starting salary will be in the range £34,220

- £36,098 per annum inclusive of London Allowance. Benefits include 30 days

annual leave and USS pension scheme. Informal enquiries may be made to Dr.

Vincenzo Nicosia at v.nicosia@qmul.ac.uk

The closing date for applications is 12th December 2019.

Interviews are expected to be held between December 2019 and the beginning of

January 2020.

The successful applicant will have an excellent knowledge and research

experience in complex networks and in dynamics on networks. In particular, it

is highly desirable that the candidate has previous research experience on

diffusion and random walks on graphs, on using high-level programming languages

to perform large-scale simulation on networks, and on analysing real-world

spatial data. The project involves the usage of random walks on graphs with

coloured nodes for the quantification of spatial heterogeneity and spatial

correlations. A track record of conducting high-quality research and writing

and publishing high-quality papers is also expected.

The position comes with a generous travel and subsistence allowance, as the

applicant is expected to visit project partners in the UK and abroad, and to

present the results of the project at international conferences in the field.

For further details of the role and selection criteria please refer to the job

specification at:


LabSchool of Mathematical Sciences, Queen Mary University of London, London
Starts on01/02/2020
Duration/Period12 months
Deadline11/12/2019 23:00
Keywordscomplex networks; spatial networks; diffusion; random walks; spatial data;

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