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We have an exciting, fully funded PhD opportunity in "Dynamic
Inferential Network Analysis for Public Health" at the University of
Glasgow. Details below. Please contact me for further information.
*Application deadline*: 12 noon, 13 January 2017
*Topic*: Dynamic Inferential Network Analysis for Public Health
- Philip Leifeld (social sciences)
- Mark McCann (public health)
- Nema Dean (maths & stats)
*Type of funding*: This is one of the prestigious Lord Kelvin Adam Smith
Scholarships at the University of Glasgow. Each year, a handful of
selected PhD scholarships are granted to the best applicants. These LKAS
scholarships are fully funded, which means that the funding includes all
tuition fees, a stipend at RCUK rates (currently £14,510 per year for
2017/18), and an annual research support budget of £3,000.
*Project summary*: The PhD candidate will work on the development and
implementation of statistical techniques for inference on longitudinal
networks and apply these techniques to datasets from the field of public
health. Many public health outcomes, such as mental health or substance
abuse, are network phenomena because they do not develop in isolation.
It is vital for public health to understand not just the prevalence, but
more importantly, also the causes of these "networked" health outcomes.
Research has suggested that people's health risk behaviour and outcomes
(e.g., smoking and obesity) may spread through networks ("contagion");
or may provoke network or friendship ties among people with similar
behaviour ("homophily"). In recent years, research in network science,
public health, the social sciences, and statistics has therefore
developed inferential network analysis techniques for modelling the
structure and dynamics of friendship or contact networks (e.g., the
Temporal Exponential Random Graph Model; TERGM) and the diffusion of
behaviour through networks over time (e.g., the Temporal Network
Autocorrelation Model; TNAM). The innovative aspect of this project is
the extension of the TERGM and the TNAM model to networks with multiple
groups, multiple relations, and/or in a co-evolutionary joint process.
This is of particular importance in public health, where behaviour like
smoking and mental health can otherwise not be explained properly.
*Project team*: The PhD student will have the opportunity to make use of
a variety of datasets in public health and work in an exciting
interdisciplinary environment. The candidate will work with supervisors
from social science research methods, public health, and statistics,
whose joint interest is the study of network dynamics. Dr Philip Leifeld
is a Senior Lecturer in Research Methods in the School of Social and
Political Sciences. His research focuses on network dynamics and
applications in the social and political sciences. Dr Mark McCann is a
Research Fellow in the Social and Public Health Sciences Unit and is an
expert in substance use, mental health, adolescent health behaviour, and
complex systems. Dr Nema Dean is a Lecturer in the School of Mathematics
and Statistics. Her research focuses on model-based inference for
dependent and high-dimensional data. The PhD project will be hosted by
the Graduate School of Social Sciences, and a stronger involvement in
any of the three disciplinary homes and institutions of the supervisors
is possible, depending on the interests of the candidate. The PhD
project will also offer the option of a research stay abroad in the
wider network of the three supervisors.
*Person specification*: This studentship is open to candidates of any
nationality -- UK, EU or International. Applicants should demonstrate
- Necessary: A strong master's degree or very strong bachelor's degree
in one of the relevant disciplines, including any of the social
sciences, public health, statistics, computer science, network science,
or related disciplines.
- Desired: An interest in, or experiences with, the analysis of
networks; an interest in public health and behaviour; a strong
background or interest in quantitative methods and statistics;
experiences in at least one programming language, such as R or C++.
- The ideal candidate enjoys interdisciplinary work and is intrinsically
motivated to learn new statistical techniques and programming languages.
*Application process*: In the first instance, prospective applicants
should contact any of the three supervisors to discuss your eligibility
([log in to unmask]; [log in to unmask];
[log in to unmask]). Applicants may submit applications up until
the application deadline of 12 noon, Friday 13 January 2017.
More details on the application procedure are available on the website
of the Lord Kelvin Adam Smith PhD Scholarship at the University of
Other PhD opportunities with me in Glasgow are available on request.
Please distribute widely. Many thanks,
Dr Philip Leifeld
Senior Lecturer in Research Methods
Director of Postgraduate Research Training
School of Social and Political Sciences
University of Glasgow
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