Postgraduate research opportunities Transparent Textual-Audio Analysis via eXplainable AI (XAI) and Natural Language Processing (NLP) for improved ESG and Impact Measurement
ApplyKey facts
- Opens: Thursday 26 January 2023
- Deadline: Friday 31 March 2023
- Number of places: 1
- Duration: 36 months
- Funding: Home fee, Stipend
Overview
The successful candidate will investigate how the use of advanced textual-audio analytics and alternative data may enhance the measurement of corporate environmental, social and governance (ESG) performance. The proposed research will develop and evaluate novel NLP-based eXplainable AI (NLP-XAI) approaches for textual-based measurement of ESG, allowing for explanations to be assigned to ESG scores and the quality of explanations to be assessed.Eligibility
Applicants should possess a strong academic track record. Specifically, we welcome applicants who have obtained, or are expected to obtain, a postgraduate degree in a data science-related subject area. We also welcome applications from candidates with a finance-related postgraduate degree who can demonstrate strong quantitative and programming skills. In exceptional cases, we will consider those without a postgraduate degree, who can demonstrate outstanding performance at undergraduate level. The successful application will be able to demonstrate a solid understanding of artificial intelligence, machine learning, and some understanding of eXplainable AI (XAI). Proficiency in languages such as Python and/or R would be desirable.
Strathclyde Business School is committed to supporting a diverse and inclusive postgraduate research population. We make decisions on entry by assessing the whole person and not relying solely on academic achievements. On that basis, please ensure that your application (via your CV and covering letter) can evidence your resourcefulness, commitment and resilience as demonstrated by broader professional and life experiences. This evidence should be centred on your ability to undertake and complete a PhD and contribute to a positive PhD community.
If English isn't your first language, you'll need an IELTS score of 6.5 or equivalent with no individual element below 5.5.
Your application must include:
- A cover letter presenting your motivation for doing a PhD and fit with the advertised research project
- An updated curriculum vitae
- Details of two academic referees, including email addresses
- Academic transcripts, which must be certified copies
Candidates for this PhD project will be selected on the basis of this information and interviews with potential supervisors.
Project Details
Environmental, Social and Governance (ESG) credentials are of growing strategic importance for businesses, with ESG investing being increasingly prioritised by investors. Accurate ESG scoring of corporations is of paramount importance. ESG scoring systems in practice, however, have major weaknesses: (1) opaqueness in the proprietary methods used by private ESG scoring agencies; (2) observed inconsistencies in the ESG scores reported by alternative private ESG scoring systems; and (3) the extent of missing ESG scores across the population of corporations. Our research project directly addresses these weaknesses.
The successful candidate will seek to develop cutting-edge methods that offer transparency, consistency, and wide applicability in ESG measurement. Specifically, the proposed research will leverage the power of Artificial Intelligence (AI), while addressing the ‘black-box' constraint of the underlying algorithms. State-of-the-art eXplainable Artificial Intelligence (XAI) techniques will be used, providing explainable outcomes. Such ‘white-box' XAI techniques will lead to transparent measurement of firms’ ESG performance, reconciliation of inconsistencies in existing ESG scoring systems, and wider application to the base of corporations.
The main contribution of this work will be the novel development and application of Natural Language Processing (NLP) based XAI approaches for textual-based measurement of ESG. Further contribution will be made by extending this work through the augmentation of textual analysis with audio characteristics of corporate earnings calls (such as manager pitch, tone and hesitancy), thus establishing an NLP classifier based on multiple modes of communication that may further enhance the reliability of our explainable ESG scoring approaches.
Funding details
Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are also eligible to apply, but they will need to find other funding sources to cover the difference between the home and international tuition fees. Exceptional international candidates may be provided funding for this difference.
Apply
Number of places: 1
There will be a shortlisting and interview process.
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Accounting and Finance
Programme: Accounting and Finance
Contact us
If you have any queries regarding this application, or would like further information, please email Dr James Bowden: james.bowden@strath.ac.uk