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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