PhD studentship available at Coventry University – Environmental modelling using Bayesian Machine Learning Methods

About the Project

Coventry University (CU) is inviting applications from suitably-qualified
graduates for a fully-funded PhD studentship, in the areas of Machine
learning, Artificial intelligence, and Environmental modelling.

Responding to risk fluctuations as a result of climate change and
assessment of relevant impacts are critical steps toward achieving many of
the UN Sustainable Development Goals. This is particularly true in regions
of the world where societal and environmental stressors are already
impacting communities and ecosystems. Many of such regions can be found
along the coastlines, where land is threatened by coastal erosion and
flooding driven by storm surges, sea-level rise and intensification of
monsoon strength, all of which are associated with climate change.
Historically, mangrove forests have mitigated against these hazards, but
mangroves have been removed or severely deteriorated due to climate change,
human activities and economic pressure.

This project will use cutting edge computational techniques to quantify the
historic and potential importance of coastal forests to resilience against
environmental hazards in the face of climate change. Central to the
project’s objectives will be to construct an efficient, scalable, accurate
and computationally-fast methodology based on the latest developments in
Bayesian machine learning (ML). The project will provide a platform for an
exceptional doctoral candidate to undertake a comprehensive piece of
research using state-of-the-art methods, spanning disciplines of data,
climate and environmental sciences.

*Training and Development*

The successful candidate will receive comprehensive research training
including technical, personal and professional skills.

All researchers at Coventry University (from PhD to Professor) are part of
the Doctoral College and Centre for Research Capability and Development,
which provides support with high-quality training and career development
activities.

*Entry criteria for applicants to PHD*

• A minimum of a 2:1 first degree in a relevant discipline/subject
area with a minimum 60{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7} mark in the project element or equivalent with a
minimum 60{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7} overall module average.

PLUS

the potential to engage in innovative research and to complete the PhD
within a 3.5 years

• a minimum of English language proficiency (IELTS overall minimum
score of 7.0 with a minimum of 6.5 in each component)

We are seeking an enthusiastic and highly motivated person with good
interpersonal skills and a keen interest in research. You must have at
least a 2:1 honours degree or a distinction or high merit at MSc level (or
international equivalent) in Mathematics, Statistics, Computer Science, or
a related quantitative discipline.

The desired candidate should also have good programming skills in Python, R
or Matlab.

For further details see:
Making an Application

To find out more about the project please contact Dr Alireza Daneshkhah (
Ali.Daneshkhah@coventry.ac.uk). To apply on line please visit:
Home Page | PGR+ Application

All applications require full supporting documentation, a covering letter,
plus a 2000-word supporting statement showing how the applicant’s expertise
and interests are relevant to the project.

Funding Notes

This is a fully funded position for three years.

Student fees for the first three years of the PhD will be waived as part of
this project. The successful candidate will receive an annual bursary.

Basic research costs (e.g. equipment) are covered by Centre for Agroecology
Water and Resilience. The successful candidate will receive an additional
allowance of £500 per annum for professional expenses.

Qualification Type: PhD
Location: Coventry University
Funding for: EU/UK Students and International Students
Hours: Full Time
Placed On: 19th October 2020
Closes: 15th November 2020