Applications are invited for fully-funded PhD studentships at Lancaster
<br>University in which you will learn to develop cutting-edge data science
<br>approaches to address key environmental science challenges.
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<br>Description of the PhD:
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<br>Understanding Trust in Environmental Data Science: Cross disciplines and
<br>cross cultures
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<br>Supervisors: Bran Knowles and Paul Young
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<br>Addressing the environmental grand challenges such as climate change,
<br>environmental pollution and biodiversity loss requires a
<br>transdisciplinary and international approach. Such collaborations have
<br>been occurring for many years, but initiatives such as the UK’s Global
<br>Challenge Research Fund (GCRF) and the international Belmont Forum have
<br>led to larger scale transdisciplinary collaborations, many of which are
<br>now occurring between the Global North and the Global South. For these
<br>collaborations to be successful, researchers will need to develop means
<br>of effectively communicating the trustworthiness of the scientific data
<br>they exchange. To understand how to facilitate this communication,
<br>research is needed regarding the strategies employed by researchers to
<br>gauge trustworthiness, including the aspects of trust that are entailed
<br>in such strategies. In particular, given the importance of the
<br>international funding landscape, are there disciplinary and/or cultural
<br>variations that need to be accommodated in cross-disciplinary and
<br>cross-cultural collaborations?
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<br>About the PhD studentships:
<br>The studentships are part of the large-scale £2.6M EPSRC-funded grant
<br>Data Science for the Natural Environment (DSNE), a joint project between
<br>Lancaster University and the NERC Centre for Ecology & Hydrology (CEH).
<br>This is an exciting opportunity to work at the heart of a
<br>multi-disciplinary team of researchers consisting of computer
<br>scientists, statisticians, environmental scientists and stakeholder
<br>organisations, working together to deliver methodological innovation in
<br>data science to tackle grand challenges around environmental change.
<br>
<br>If learning to develop and deploy data science techniques to solve the
<br>biggest problems faced by humanity is an appealing next step, please
<br>send a letter of application to dsne@lancaster.ac.uk by 5pm on Monday
<br>11th February. Unfortunately, while we can cover the full fees and
<br>stipend of UK/EU applicants, the full fee of non-EU applicants cannot be
<br>covered. The letter should include:
<br>
<br>1. An ordered list of which of the PhD projects you would like to be
<br>considered for, with an explanation of your reasoning
<br>2. An explanation of why your skill set and previous education will
<br>allow you to be successful in these projects (a transcript of your
<br>undergraduate or masters degree programme is likely to be helpful)
<br>
<br>To be able to answer these questions sensibly, it is advisable to talk
<br>to the supervisors of your desired projects, in advance of submitting
<br>your application.
<br>
<br>Unfortunately, while we can cover the full fees and stipend of UK/EU
<br>applicants, the full fee of non-EU applicants cannot be covered.
<br>
<br>Extended submission deadline is the 12th of April, 2019.
<br>
<br>PhD topics are available across the spectrum of DSNE research, including
<br>social science aspects, for more information please visit:
<br>
<br>https://www.lancaster.ac.uk/data-science-of-the-natural-environment/studentships/#understanding-trust-in-environmental-data-science:-cross-disciplines-and-cross-cultures
<br>
<br>For inquires about the advertised PhD projects, please contact Dr Bran
<br>Knowles:
<br>
<br>b.h.knowles1@lancaster.ac.uk
<br>https://www.lancaster.ac.uk/people-profiles/bran-knowles
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