PhD on Audits for Explainability and transparency for AI Software (0.8 - 1.0 FTE)

Jheronimus Academy of Data Science (JADS) Den Bosch, is proud to start with three large Robust AI labs together with:

1. Deloitte (Auditing for Responsible AI Software Systems) - 5 PhD's
2. DPG Media (Responsible Media Lab) - 5 PhD's together with University of Amsterdam (UvA)
3. ILUSTRE (Innovation Lab for Utilities on Sustainable Technology and Renewable Energy) - 5 PhD's

JADS is seeking enthusiastic colleagues for the position of PhD students. We operationalize the huge ambition around AI by explicitly aligning our research agenda on Robust AI with the United Nation's sustainable development goals.
The project is funded in a public-private partnership by NWO/NLAIC and the private partners. This position is part of the Deloitte project.

Short Description 
The next generation of enterprise applications is quickly becoming AI-enabled, providing novel functionalities with unprecedented levels of automation and intelligence. As we recover, reopen, and rebuild, it is time to rethink the importance of trust. At no time has it been more tested or valued in leaders and each other. Trust is the basis for connection. Trust is all-encompassing: physical, emotional, digital, financial, and ethical. A nice-to-have is now a must-have; a principle is now a catalyst; a value is now invaluable.

Are you an enthusiastic and ambitious researcher with a completed master's degree in a field related to machine learning (Computer science, AI, Data Science) or in Electrical Engineering with an affinity for AI and deep learning? Does the idea of working on real-world problems and with industry partners excite you? Are you passionate about using trustworthy AI methods for the next generation of auditing processes, which are increasingly AI-enabled and data-driven? And are you interested in delivering new tools to ascertain the explainability and transparency of the next generation of AI software?

We are recruiting a PhD candidate who will develop and validate novel concepts, methods, and tools for monitoring, auditing, and fostering explainability and transparency of AI software systems and trial them with industrial partners who work with Deloitte.

Job Description
This vacancy falls under the auspices of the JADE lab, which is the data/AI engineering and governance research UNIT of the JADS, and DELOITTE.  In particular, this position is associated with  JADE's ROBUST program on Auditing for Responsible AI Software System (SAFE-GUARD), which is financed under the NWO LTP funding scheme with Deloitte as the key industry partner. 

Whilst the overall objective of SAFE-GUARD is auditing of AI software, it may be further refined in the following more elaborated goal: "Explore, develop and validate novel auditing theories, tools, and methodologies that will be able to monitor and audit whether AI applications adhere in terms of fairness (no bias), explainability, and transparency (easy to explain), robustness and reliability (delivering same results under various execution environments), respect of privacy (respecting GDPR), and safety and security (with no vulnerabilities)."

The industrial setting of the deep involvement of Deloitte will balance the rigour with relevance and ascertain fit with societal requirements and trends, validation with industrial case studies.

Scientific Challenge
Explainability and transparency have been recognized as fundamental aspects of responsible AI systems. Considering these aspects ensures the reliability of the AI model when making decisions that, for example, are not based on sex or race or any other data point they wish to make ambiguous that can have disastrous consequences.

Therefore, Deloitte calls for transparency and responsibility in AI. Transparent AI software explicates (implicit) underlying values, including ethical and moral considerations, and promotes the responsibility of companies or AI-software-based decisions. At the same time, ensuring and assessing system explainability in applied contexts is a daunting task, involving various stakeholders (developers, users, owners), and perspectives (technical, legal, psychological, economics).

This project aims at improving the assessment of explainability and transparency of business/governmental decisions that are (partially) based on AI software, such as job offers, loan proposals, etc. As such, it goes way beyond simply publishing the AI code, as suggested by many, and aims at opening the AI software 'black box' and explaining whether or not the AI algorithms make sense, are well tested, and audited. At the same time, explainability involves a balancing act of explaining the workings in laymen's terms against oversimplification. Therefore, part of this project is the development of a toolbox for auditors (and their clients) to help evaluate the transparency and explainability against a coherent set of measurable parameters and suggest improvements.

Candidates should:

• have a MSc in Mathematics, Statistics, Computer Science, Computer Engineering, AI or a related discipline;
• have a strong interest in data engineering and governance, machine-learning and deep-learning;
• have excellent programming skills and be highly motivated, be rigorous and disciplined when developing algorithms and software according to high quality standards;
• have good technical understanding of the statistical models used in data science and machine learning;
• have knowledge of, or a willingness to familiarize themselves with, current research into machine learning for software engineering trustworthiness evaluation;
• have a commitment to develop algorithms that analyze Big Data from software-defined infrastructures as well as AI application code;
• be a fast learner, autonomous and creative, show dedication and be hard working;
• possess good communication capabilities and be an efficient team worker;
• be fluent in English, both spoken and written.

Being appointed at JADS provides a meaningful job in a dynamic and ambitious community of 2 universities and startups. Based on the project, the candidate receives an appointment at TU/Eindhoven or Tilburg University.

As a PhD Student at JADS you will have a full-time employment for a total of four years, with an intermediate evaluation after nine months. JADS offers excellent employment conditions with attention to flexibility and (personal) development and attractive fringe benefits. The gross monthly salary is in accordance with the Collective Labor Agreement for Dutch Universities. The minimum gross salary is € 2.541 per month up to a maximum of € 3.247 in the fourth year;

You are entitled to a vacation allowance of 8% and a year-end bonus of 8.3% of your gross annual income. If you work 40 hours per week, you will receive 41 paid days of leave per year. PhD Students from outside the Netherlands may qualify for a tax-free allowance of 30% of their taxable salary if they meet the relevant conditions. The university applies for this allowance on their behalf. JADS will provide assistance in finding suitable accommodation.

Preferred starting date: August 1, 2023.

To develop your teaching skills, you will spend 10% of your employment on teaching tasks. To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students.
Next to that we offer all kinds of facilities and arrangements to maintain an optimal balance between work and private life. All employees of the university are covered by the so-called General Pension Fund for Public Employers (Stichting Pensioenfonds ABP).  

JADS values an open and inclusive culture. We embrace diversity and encourage the mutual integration of groups of employees and students. We focus on creating equal opportunities for all our employees and students so that everyone feels at home in our university community. 
All researchers working in JADS have contracts at either Tilburg University or Eindhoven University of Technology. Please visit Working at Tilburg University and Working at Eindhoven University of Technology for more information on their respective employment conditions.