Apologies if you receive multiple copies of this message.

We currently have two PhD positions and one postdoc position to fill at the 
Laboratory for Foundations of Computer Science at the University of Edinburgh.
The funding for these posts comes from a European project (QUANTICOL) on 
quantitative modelling of collective adaptive systems. The postdoc and the PhD 
students will be expected to participate in this project and work towards the 
project goals and objectives, contributing to tasks and deliverables and 
working with other researchers involved in the project. A strong background in 
formal languages, mathematics and programming will be needed in all cases.
The details are given below.  Please can you circulate this information to 
anyone in your group or department who you think might be interested.

  Research Associate

 Fixed Term 36 months

 Vacancy Reference No: 009803

We have an opening for one research associate position in quantitative 
modelling of complex adaptive systems (CAS). These consist of a large number of 
heterogeneous entities with decentralised control and varying degrees of 
complex autonomous behaviour.  Examples include smart urban transport systems 
and smart grids. The successful candidate is expected to have a strong research 
background with several years of experience in scalable analysis and 
verification techniques. The candidate must either already have a PhD in a 
relevant area or be nearing completion of their PhD studies, and must have a 
track record of related publications. Excellent skills in programming are 
essential. It is also preferable to have a detailed working knowledge of 
stochastic process algebras and their associated modelling tools and 
verification techniques. Candidates with expertise in simulation, continuous 
approximation, mean field approximation, or control theory will be preferred.
The post is available from 1st April 2013 for 36 months and is on the UE07 
scale (£30,122 - £35,938)

See http://bit.ly/X8N7yQ for further details.  The deadline for applications is 
1st March 2013.
Note that in this case formal applications must be made through the webpage 
http://bit.ly/X8N7yQ 

  PhD Studentship: Parameter and Model Fitting for Spatial Data

 36 months

We are seeking to award a PhD studentship on the topic of parameter and model 
fitting for spatial data in the context of modelling complex adaptive systems.

The PhD studentship is fully funded for three years at EU student fee level. 
The project will be supervised by Professor Stephen Gilmore of the School of 
Informatics at the University of Edinburgh.

Parameter estimation is an algorithmic procedure which seeks to find model 
parameters (such as rates and probabilities) which make the results computed 
from a mathematical model agree with a dataset obtained by measurement and 
observation. Algorithmic or heuristic search procedures are applied to 
investigate the multi-dimensional space of possible parameter values and the 
search for good parameter values is guided by a cost function which assigns a 
numerical value to the difference between the results computed by the model and 
the data which has been recorded. The search for model parameters is usually 
complicated by the fact that the data which is being considered includes some 
noise due to measurement error and there is no comparable noise in the model.
The goal of this project is to investigate the role of spatial data in fitting 
formal models which contain an explicit representation of space. Spatial 
information adds another degree of complexity to the model and places 
constraints on the parameter optimisation process. For example, we may know 
that activity rates at one location are a simple function of rates at another 
location, but we may not know the multiplicative constants which are used to 
scale the rates. Spatial information such as this allows the possibility of a 
structured approach to parameter fitting which operates by first using 
clustering to identify patches in space where sets of parameters are 
applicable. This is then followed by a phase which attempts to fit parameters 
on a per-patch basis. That in turn is followed by a phase which attempts to 
integrate patches and combine parameter sets.
To apply contact Stephen Gilmore directly ([email protected]). Attach a 
CV, transcript, and a brief statement explaining why you are a good match for 
this scholarship. The formal application will require a 1-2 page research 
proposal; you may attach a draft.  
The deadline for applications is 20th February 2013.
http://www.ed.ac.uk/schools-departments/informatics/postgraduate/fees/research-grant-funding/parameterandmodelfitting


  PhD Studentship: Spatial modelling of complex adaptive systems

 36 months

We are seeking to award a PhD studentship on the topic of stochastic process 
algebras for spatial modelling in the context of modelling complex adaptive 
systems.The PhD studentship is fully funded for three years at EU student fee 
level. The project will be supervised by Professor Jane Hillston of the School 
of Informatics at the University of Edinburgh.

Our goal is to develop novel, scalable formal modelling and analysis techniques 
for complex adaptive systems consisting of large numbers of autonomous 
heterogeneous components. In particular we are interested in systems in which 
the spatial organisation of components influences the emergent behaviour and 
therefore cannot be abstracted away. Stochastic process algebras have been 
successfully applied to model a wide range of complex systems comprised of 
interacting populations of components, and associated mean field techniques 
allow scalable analysis of these systems. The goal of this project is to extend 
stochastic process algebras to express systems with a spatial aspect and 
develop appropriate scalable analysis techniques. Working with others you will 
help to develop a methodological framework for spatial modelling based on sound 
mathematical foundations, and then embed the approach in a stochastic process 
algebra language using appropriate formal constructs. These constructs will 
then be linked to exact and approximate analysis techniques from the literature 
and developed elsewhere in the QUANTICOL project. The developed techniques will 
be implemented in software prototypes. To make this more concrete the work will 
focus on case studies based on smart urban transportation and smart grids.

To apply contact Jane Hillston directly ([email protected]). Attach a CV, 
transcript, and a brief statement explaining why you are a good match for this 
scholarship. The formal application will require a 1-2 page research proposal; 
you may attach a draft.  
The deadline for applications is 20th February 2013.
http://www.ed.ac.uk/schools-departments/informatics/postgraduate/fees/research-grant-funding/spatialmodelling


The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
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