PhD on Auditing Framework & tool for robust and reliable AI software DevOps

PhD on Auditing Framework & tool for robust and reliable AI software DevOps
PhD on Auditing Framework & tool for robust and reliable AI software DevOps

Published	Deadline	Location
yesterday	23 Apr	Eindhoven

Job description
PhD on Auditing Framework and tool for robust and reliable AI software development and operations (DevOps) (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:

Deloitte (Auditing for Responsible AI Software Systems) - 5 PhD's

DPG Media (Responsible Media Lab) - 5 PhD's together with University of Amsterdam (UvA)

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 robustness and reliability 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 the robustness and reliability 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 rigor with relevance and ascertain fit with societal requirements and trends, validation with industrial case studies.
Scientific Challenge
Like DevOps, MLOps adopts the continuous integration and continuous testing cycle to produce and deploy production-ready new micro-releases and versions of AI software. This implies a culture shift between data analysts, data engineers, deployment and system engineers, and domain experts, with improved dependency management (and thus transparency) between model development, training, validation, and deployment. In addition, MLOps requires sophisticated policies based on metrics and telemetry such as performance indicators like F1, accuracy scores, and software quality.
At the same time, AI models are trained to assume that data used is representative of future data, i.e., input data is independently and identically distributed. This implies that random and noisy input data corruptions can lead to a lack of robustness. From here, the need to provide an instrument able to maintain the robustness of AI models when new data comes and to realize a new version with the same reliability value.
Specifications

• max. 30.4 hours per week
• Eindhoven View on Google Maps

Eindhoven University of Technology (TU/e)

Requirements
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.

Conditions of employment
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.
Additional information
More information 
Do you recognize yourself in this profile and would you like to know more? Please contact: 

• Prof. Willem Jan Van Den Heuvel, [email protected] 
• Prof. Damian A. Tamburri, [email protected] 

For information about terms of employment, please contact Marielle van Gerven, HR Advisor,
[email protected] or +31 40 247 3699.
Application
We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• Brief description of your MSc thesis and any potential scientific article you have published.

We look forward to your application and will screen it as soon as we have received it.
First Deadline: April 23, 2023. The screening will continue until the position has been filled.
Security checks can be part of the selection procedure and admission to a lab, both by the university as an employer and by the companies the lab collaborates with.
Note: CHECK OUT THE OTHER PhD vacancies at JADS!
JADS
We do cool stuff that matters, with data. The Jheronimus Academy of Data Science (JADS)  is a unique cooperation between Eindhoven University of Technology (TU/e) and Tilburg University (TiU). At JADS, we believe that data science can provide answers to society's complex issues. We provide innovative educational programs, data science research, and support for business and society. With a team of lecturers, students, scientists and entrepreneurs - from a wide range of sectors and disciplines - we work on creating impact with data science. We do this by connecting people, sectors and industries: in the past 5 years we have been working with 300+ organizations on data-related projects. Our main drivers? Doing cool stuff that matters with data. Our location at the former monastery Mariënburg in Den Bosch houses a vibrant campus fully dedicated to data science. 
Recruitment code
Tilburg University applies the recruitmentcode   of the Dutch Association for Personnel Management & Organization Development (NVP).
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