DoctorateFaculty of Business and Economics

PhD in Accounting

Welcome, future masters of the global economy. In this program, we will not just learn to predict the future, but to understand the forces that shape it. Let's build the systems that can truly understand the world.

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Level: Doctorate
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Financial Reporting, Auditing, Taxation, Corporate Finance

Practical focus

Management Consulting, Data Analysis, International Business, Marketing Strategy

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

The British Library
Internships in digital archives and preservation
The Guggenheim Museum
Opportunities in digital humanities and curation
The National Archives
Internships in archival science

Career opportunities

Senior Data Scientist
In a tech, finance, or government
Business Intelligence Architect
Designing data systems for businesses
Policy Analyst
Using data to inform government or NGO decisions
Research Scientist
In academia or industry

Jobs and projects

Problem-Solving
Applying a systematic approach to data-driven challenges
Programming
Competency in statistical languages like R or Python
Attention to Detail
Meticulousness in data cleaning and analysis
Ethical Reasoning
Understanding the ethical implications of data use

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- You will gain a deep understanding of how to use data to improve human health, with a skill set that is in high demand in the rapidly growing field of personalized medicine and diagnostics.
Skills you build
- Statistical Learning: Proficiency in advanced machine learning and statistical models.
- Causal Inference: Understanding the cause-and-effect relationships in data.
- Decision Theory: Applying statistical principles to make optimal decisions.
- Big Data Analytics: Skills in extracting valuable patterns from large datasets.

Listed courses

Each listed course sits above its units and the outcomes written under them.

PhD in Accounting

01Advanced Financial Reporting
1. FoundationsFoundations of Advanced Financial Reporting
  The learner can you will gain a deep understanding of how to use data to improve human health, with a skill set that is in high demand in the rapidly growing field of personalized medicine and diagnostics, as applied to Advanced Financial Reporting.
  The learner can distinguish related ideas inside Advanced Financial Reporting.
2. MethodsMethods in Advanced Financial Reporting
  The learner can apply a method from Advanced Financial Reporting to a documented case.
  The learner can select an appropriate method from Advanced Financial Reporting for a stated problem.
3. ApplicationApplication of Advanced Financial Reporting
  The learner can evaluate a practice of Advanced Financial Reporting against a stated criterion.
  The learner can transfer Advanced Financial Reporting to a new documented context.
02Auditing and Financial Reporting
1. FoundationsFoundations of Auditing and Financial Reporting
  The learner can explain the core terms of Auditing and Financial Reporting.
  The learner can distinguish related ideas inside Auditing and Financial Reporting.
2. MethodsMethods in Auditing and Financial Reporting
  The learner can apply a method from Auditing and Financial Reporting to a documented case.
  The learner can select an appropriate method from Auditing and Financial Reporting for a stated problem.
3. ApplicationApplication of Auditing and Financial Reporting
  The learner can evaluate a practice of Auditing and Financial Reporting against a stated criterion.
  The learner can transfer Auditing and Financial Reporting to a new documented context.
03Taxation
1. FoundationsFoundations of Taxation
  The learner can explain the core terms of Taxation.
  The learner can distinguish related ideas inside Taxation.
2. MethodsMethods in Taxation
  The learner can apply a method from Taxation to a documented case.
  The learner can select an appropriate method from Taxation for a stated problem.
3. ApplicationApplication of Taxation
  The learner can evaluate a practice of Taxation against a stated criterion.
  The learner can transfer Taxation to a new documented context.
04Corporate Finance
1. FoundationsFoundations of Corporate Finance
  The learner can explain the core terms of Corporate Finance.
  The learner can distinguish related ideas inside Corporate Finance.
2. MethodsMethods in Corporate Finance
  The learner can apply a method from Corporate Finance to a documented case.
  The learner can select an appropriate method from Corporate Finance for a stated problem.
3. ApplicationApplication of Corporate Finance
  The learner can evaluate a practice of Corporate Finance against a stated criterion.
  The learner can transfer Corporate Finance to a new documented context.
05Research Seminar in Accounting
1. FoundationsFoundations of Research Seminar in Accounting
  The learner can explain the core terms of Research Seminar in Accounting.
  The learner can distinguish related ideas inside Research Seminar in Accounting.
2. MethodsMethods in Research Seminar in Accounting
  The learner can apply a method from Research Seminar in Accounting to a documented case.
  The learner can select an appropriate method from Research Seminar in Accounting for a stated problem.
3. ApplicationApplication of Research Seminar in Accounting
  The learner can evaluate a practice of Research Seminar in Accounting against a stated criterion.
  The learner can transfer Research Seminar in Accounting to a new documented context.
06The Practical Guide to Digital History
1. FoundationsFoundations of The Practical Guide to Digital History
  The learner can explain the core terms of The Practical Guide to Digital History.
  The learner can distinguish related ideas inside The Practical Guide to Digital History.
2. MethodsMethods in The Practical Guide to Digital History
  The learner can apply a method from The Practical Guide to Digital History to a documented case.
  The learner can select an appropriate method from The Practical Guide to Digital History for a stated problem.
3. ApplicationApplication of The Practical Guide to Digital History
  The learner can evaluate a practice of The Practical Guide to Digital History against a stated criterion.
  The learner can transfer The Practical Guide to Digital History to a new documented context.
07Archival Science for Public Policy
1. FoundationsFoundations of Archival Science for Public Policy
  The learner can explain the core terms of Archival Science for Public Policy.
  The learner can distinguish related ideas inside Archival Science for Public Policy.
2. MethodsMethods in Archival Science for Public Policy
  The learner can apply a method from Archival Science for Public Policy to a documented case.
  The learner can select an appropriate method from Archival Science for Public Policy for a stated problem.
3. ApplicationApplication of Archival Science for Public Policy
  The learner can evaluate a practice of Archival Science for Public Policy against a stated criterion.
  The learner can transfer Archival Science for Public Policy to a new documented context.
08Capstone Project in Historical Analysis
1. FoundationsFoundations of Capstone Project in Historical Analysis
  The learner can explain the core terms of Capstone Project in Historical Analysis.
  The learner can distinguish related ideas inside Capstone Project in Historical Analysis.
2. MethodsMethods in Capstone Project in Historical Analysis
  The learner can apply a method from Capstone Project in Historical Analysis to a documented case.
  The learner can select an appropriate method from Capstone Project in Historical Analysis for a stated problem.
3. ApplicationApplication of Capstone Project in Historical Analysis
  The learner can evaluate a practice of Capstone Project in Historical Analysis against a stated criterion.
  The learner can transfer Capstone Project in Historical Analysis to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

I am a financial analyst who believes that the most complex systems we will ever study are financial markets. My work focuses on mastering the principles of financial management, investment analysis, and capital markets to make sound financial decisions.

Applied mentorship

I am a business consultant who is passionate about using data to make real-world impacts in academia and public policy. My mentorship focuses on helping students apply their skills to clinical and research problems, turning raw data into actionable insights.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

• Blog Post: 'Beyond Prediction: The Dawn of Causal AI' - An accessible essay on the growing field of causal inference and its importance for the future of AI. · • Blog Post: 'The Statistical Fallacies of A/B Testing' - Discusses the common pitfalls of A/B testing and how causal inference can lead to better business decisions. · • Conference Paper: 'A New Method for Causal Inference in High-Dimensional Data' - Presented at the International Conference on Machine Learning, detailing a breakthrough in understanding causality in complex systems. · • Journal Article: 'Causal Inference for Fair and Transparent Machine Learning' - Published in the Journal of Statistical Science, this paper provides a framework for designing AI systems that are both powerful and ethical. · • Standard Article: 'A Look at the Future of Causal Analytics in Public Policy' - A multi-part series for a policy magazine on how causal models are transforming public policy. · • Book: 'The Causal Inference Handbook' - A comprehensive textbook on the theoretical and practical applications of causal inference. · • Total Score: 29/30 · • Kairos Badge: 🥇

R / 02

Mentor practice lens

• Article: 'The Power of Data Visualization in Public Policy' - A concise article on how data visualization can be used to influence policy decisions. · • Guide: 'A Beginner's Guide to Using R for Historical Data Analysis' - A practical tutorial for new students on the basics of a key bioinformatics programming language. · • Essay: 'Building Ethical AI for Public Policy' - An essay on the challenges and responsibilities of creating AI tools for government. · • Total Score: 28/30 · • Kairos Badge: 🥇

Adaptive capability

Professor superpower

GAF-powered Causal Pathway Visualization

Adaptive capability

Mentor superpower

GAF-powered Clinical Insight Extraction

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. George Pendleton

Financial Reporting, Auditing, Taxation, Corporate Finance

Meet your professor Open the classroom

AI Super Mentor

Dr. Irina Volkov

Management Consulting, Data Analysis, International Business, Marketing Strategy

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Adapted. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor	Master	Doctorate This programme
9 months · Fast track	12000 EUR	9600 EUR	12000 EUR
12 months · Recommended	14400 EUR	12000 EUR	14400 EUR
15 months · Standard	16800 EUR	14400 EUR	16800 EUR
18 months · Flexible	19200 EUR	16800 EUR	19200 EUR
21 months · Extended	21600 EUR	19200 EUR	21600 EUR
24 months · Part-time	24000 EUR	21600 EUR	24000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

Named tuition lists Add-on services

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PhD in Accounting

Academic focus

Practical focus

The British Library

The Guggenheim Museum

The National Archives

Senior Data Scientist

Business Intelligence Architect

Policy Analyst

Research Scientist

Problem-Solving

Programming

Attention to Detail

Ethical Reasoning

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. George Pendleton

Dr. Irina Volkov

Find the program that expands your universe.