Applications are invited for fully-funded PhD studentships at Lancaster
University in which you will learn to develop cutting-edge data science
approaches to address key environmental science challenges.
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Description of the PhD:
Decision Making in the Face of Uncertainty: A Qualitative Study
Supervisors: Bran Knowles and Gordon Blair
The DSNE Project is seeking to address three grand challenges of the
natural environment through the development of novel data science
methods, including a combination of machine learning and statistical
techniques all within a Bayesian framework. The aim is to support
decision making under uncertainty and to derive techniques which both
quantify and constrain this uncertainty, arguably the holy grail of
environmental science. In the project, we are working closely with a
range of stakeholders and it is important to understand the how
stakeholders derive valid and actionable conclusions from the underlying
data science. To identify strategies for cultivating such
understandings, qualitative research is needed about the basis for
assumptions used by stakeholders in interpreting uncertainty and what
factors influence these assumptions. Through ethnographic study of the
three grand challenges being undertaken as part of DSNE, this
studentship will investigate stakeholders’ evolving conceptions of
uncertainty over a period of engagement with data scientists. The
successful student will develop their own research questions, but we
expect a multidisciplinary approach drawing on theories of uncertainty,
with investigations including how stakeholders think about, handle, or
even make use of uncertainty in data and data science.
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About the PhD studentships:
The studentships are part of the large-scale £2.6M EPSRC-funded grant
Data Science for the Natural Environment (DSNE), a joint project between
Lancaster University and the NERC Centre for Ecology & Hydrology (CEH).
This is an exciting opportunity to work at the heart of a
multi-disciplinary team of researchers consisting of computer
scientists, statisticians, environmental scientists and stakeholder
organisations, working together to deliver methodological innovation in
data science to tackle grand challenges around environmental change.
If learning to develop and deploy data science techniques to solve the
biggest problems faced by humanity is an appealing next step, please
send a letter of application to dsne@lancaster.ac.uk by 5pm on Monday
11th February. Unfortunately, while we can cover the full fees and
stipend of UK/EU applicants, the full fee of non-EU applicants cannot be
covered. The letter should include:
1. An ordered list of which of the PhD projects you would like to be
considered for, with an explanation of your reasoning
2. An explanation of why your skill set and previous education will
allow you to be successful in these projects (a transcript of your
undergraduate or masters degree programme is likely to be helpful).
To be able to answer these questions sensibly, it is advisable to talk
to the supervisors of your desired projects, in advance of submitting
your application.
Unfortunately, while we can cover the full fees and stipend of UK/EU
applicants, the full fee of non-EU applicants cannot be covered.
Extended submission deadline is the 12th of April, 2019.
PhD topics are available across the spectrum of DSNE research, including
social science aspects, for more information please visit:
https://www.lancaster.ac.uk/data-science-of-the-natural-environment/studentships/#understanding-trust-in-environmental-data-science:-cross-disciplines-and-cross-cultures
For inquires about the advertised PhD projects, please contact Dr Bran
Knowles:
b.h.knowles1@lancaster.ac.uk
https://www.lancaster.ac.uk/people-profiles/bran-knowles
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