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I'm searching for a PhD candidate to join my group at the University of
Bath, UK. The project description is available at
https://skewed.de/tiago/phd, and is attached below. The deadline for the
application is November 30th, 2017.
I'm looking for strong people with a background in statistical physics and
Please forward as appropriate!
PhD position: “Inferring the evolutionary forces shaping the structure and
function of complex network systems”
Department of Mathematical Sciences, University of Bath, UK
Centre for Networks and Collective Behaviour
Supervisor: Dr. Tiago P. Peixoto
Application deadline: November 30th, 2017
An enormous variety of complex systems shares the unifying property that
they can be mathematically modelled as a network of interacting elements.
Examples of this include social iterations, communication systems, cell
metabolism, transportation infrastructure, among many others. Despite the
different domains, all these systems can be modelled at their most
fundamental level under the same network formalism. With the aim of
exploiting this universality, a great deal of transdisciplinary research has
been devoted to developing general network models that are valid across
The aim of this PhD project is to move towards this goal using a specific
blend of mathematical modelling and data analysis, based heavily on concepts
and analytical tools from Statistical Physics, and employing a variety of
approaches from Bayesian Inference and Machine Learning. In particular, the
main objectives are:
1. Elaboration of generative models of networks that take into account key
evolutionary aspects (e.g. optimization towards robustness under
constraints, homophily, incremental growth dynamics), and yield credible
descriptors of large-scale network structure (e.g. modular organization,
hierarchies and centralization).
2. Development of principled inference methods that can extract model
parameters from real-world network data via efficient algorithms, as well as
model selection approaches that can identify the most appropriate generative
process based on empirical evidence.
3. Employment of the modelling and inference frameworks to make predictions
that generalise from past observations, identify errors and omissions in
data, as well as opportunities for architectural improvements.
The combination of these three objectives would yield concrete connections
between the structure, function and evolution of network systems, with
potential applications as diverse as preventing the outbreak of diseases and
traffic jams, discovering new interactions between drugs, and building a
Furthermore, the diverse and multidisciplinary nature of the research would
give the candidate many options in further pursuing an academic career in
Theoretical Physics, Machine Learning and Data Science, as well as
opportunities for applications in industry.
The successful candidate should be highly motivated and have a degree in
Physics, Applied Mathematics or related fields. Demonstrable familiarity
with mathematical modelling as well as computational skills (C/C++ and/or
Python) is essential.
The position is for 3.5 years of full-time study and will administratively
belong to the Department of Mathematical Sciences at the University of Bath,
associated with the Centre for Networks and Collective Behaviour, and will
be supervised by Dr. Tiago Peixoto.
The application deadline is November 30th, 2017, and the successful
candidate will be ready to start by March 2018 at the latest. Applications
should be done online, via the Doctoral College:
Please mention the name of the project and supervisor in your application.
Informal inquiries should be directed to Dr. Tiago Peixoto
([log in to unmask]).
Applications may close early if a suitable candidate is found; therefore,
early application is recommended.
EU students applying for this project may be considered for a University
Research Studentship which will cover UK/EU tuition fees, a training support
fee of £1000 per annum and a tax-free maintenance allowance of £14,296
(2016/17 rate) for 3.5 years.
Note: ONLY EU applicants are eligible for the studentship; unfortunately,
applicants who are classed as Overseas for fee paying purposes are NOT
eligible for funding.
Tiago de Paula Peixoto <[log in to unmask]>
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