This project is linked to our new PhD in Financial Technology programme, specifically around the theme of environmental risks in supply chain networks.
|Deadline||The deadline for this scholarship has now passed|
UK/EU and Overseas tuition fees plus £20,000 stipend awarded annually for up to 4 years
|Contact||Email Email Scholarship Support Team|
This project will study how environmental risks affect supply chain networks and how firms can best adapt their supply chain to protect it against those risks. Specifically, it will combine Artificial Intelligence and Robust Optimisation techniques to study the effects of environmental risks on the supply chain networks and suggest alterations that can make supply chains less vulnerable to environmental shocks and climate change.
In the age of globalisation, most firms operate globalised production and supply chain networks, currently optimised for cost. However, global supply chains often move through the parts of the world that are most vulnerable to climate change impact. All economies are now becoming aware of new environmental constraints as we hit the 'limits to conventional growth'. In this context, there is an urgency to understand how firms can fundamentally adapt to both climate change and new environmental resource considerations.
Environmental, social, and corporate governance (ESG) data on the complex supply chains that is the feature of industrial activities in this age remains woefully inadequate to allow for the exploration of how business operations are affected by climate change and other environmental constraints. Combining supply chain network data with relevant ESG data at each point along the network potentially offers powerful insights on how exposed supply chain networks are to environmental and other pertinent risks. Using Artificial Intelligence techniques, the combined data can be exploited to quantify the risks at different levels within the supply chain. In addition, robust optimisation techniques can be used to suggest adjustments that can be made within supply chains in order to minimise the impact of environmental resource constraints, climate shocks, and vulnerabilities.
Meet the PhD programme academic requirements. This normally requires a minimum qualification (or expected qualification if you are a current Master's student) of above-average academic achievement, quantified as 70% or above overall at the Masters level, with a distinction level dissertation (or UK equivalent) in the subject of: operations research, finance, economics, informatics, physics, mathematics, engineering, or another relevant programme with significant quantitative elements.
Students with significant finance and tech industry experience or with relevant professional qualifications and that also have a minimum of a Bachelor's degree in the programmes stated above will be given due consideration on a case-by-case basis.
The most commonly approved certificate is an IELTS, for which the minimum accepted score is 7.0 overall with at least 6.0 in each section.
Other Essential Criteria
- Strong quantitative skills demonstrated by academic excellence or practical experience
- Programming skills in at least two of the following languages:
- Demonstrable experience in data analysis using popular machine-learning models
- Knowledge of network theory or experience in analysing complex network data
The scholarship will cover UK/EU fees, and will provide a £20,000 stipend annually for up to four years.
How to Apply
In order to apply for this opportunity you must apply to the PhD in Financial Technology programme, making sure to include a cover letter detailing why you are the right candidate for this project. As this opportunity has a project already in place you do not need to submit a research proposal.
To find out what documents are required when submitting an application to the PhD in Financial Technology programme, please see our documents guide:
The deadline to apply is 23:59 (GMT) on 3 May 2020.
Eligible applicants will be ranked by a selection panel and applicants will be notified if they have been shortlisted for interview.
Interviews are anticipated to be scheduled mid-May 2020.
Please note that this scholarship award is subject to candidates successfully securing admission to the PhD in Financial Technology programme at the University of Edinburgh. If an awarded candidate has a conditional offer onto the programme, they must fulfil this condition before starting their studies.
Dr Belen Martin-Barragan
+44 (0)131 651 5539
Lindsey Singleton, Postgraduate Research Support and Development Officer
+44 (0)131 651 5337
Dr Luca Taschini
University of Edinburgh Business School
29 Buccleuch Place