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’s time to rethink the importance of trust. At no time has it been more tested or more 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.

The SAFEGUARD lab forges a unique collaboration between Tilburg University, Eindhoven University of Technology, the Jheronimus Academy for Data Science (JADS), and Deloitte. Essentially, this lab focuses on the development, validation and valorization of state-of-the-art, AI-enabled tools to help the next generation of auditors to automatically, continuously and transparently check, ensure and certificate the trustworthiness of AI-applications. The SAFEGAURD lab will synergistically unite software engineering and AI into AI Engineering, fusing proven software development practices (including data pipeline tool chains, and data governance) with the full range of AI, from machine- to advanced deep learning. In this way, it can be ascertained that AI-enabled enterprise systems are trustworthy implying they are fair, explainable and transparent, responsible and accountable, robust and reliable, respectful of privacy, and safe and secure. The SAFEGUARD project is a collaboration of the Jheronimus Academy of Data Science (JADS), 's-Hertogenbosch (campus Mariënburg), Tilburg University (TiU), Eindhoven University of Technology (TU/e) and Deloitte, with the intent of delivering competitive technology and AI Software Engineering assets to address the above. 

In this respect, JADS is looking for a skilled research professional with whom to share the coordinating roles as well as advisory functions to be employed across the aforementioned lab and its intended research and educational initiatives. The role in question will also likely involve dissemination, exploitation, and further development of concepts, theories, and practices developed within lab operations, for example, at the level of followup projects at NL and EU level.

Profile
The research will be conducted under supervision of Prof. Dr. Willem-Jan van den Heuvel and Dr. Damian A. Tamburri. The successful assistant professors are expected to deliver both long-term results (long-term research agendas spanning the JADS user networks) and mid-term results (e.g., publishable algorithms, datasets, approaches, high-impact/high-relevance papers, best practices, patents, etc.).

The successful candidate is expected to:

• Perform and coordinate scientific research in the domain described;
• Advise SAFEGUARD Ph.D. students in bootstrapping and executing their own research avenues;
• Develop or supervise the development of best-practices, datasets, software, and other components that address the lab operational needs;
• Present results at (international) conferences and engage in appropriate international communities;
• Publish mature results in scientific journals;
• Educate students both within the SAFEGUARD lab and beyond, up to the overall JADS studentship, e.g., as part of the involvement in 1-2 JADS courses for a total of at least 12 ECTS;
• Participate in activities of the JADS Data and Engineering (JADE) unit, mainly in 's-Hertogenbosch but sometimes also in Eindhoven or Tilburg or at one of the commercial partners in several locations in Europe.

Candidates should:

• Have a PhD. in Mathematics, Statistics, Computer Science, Computer Engineering, AI or a related discipline;
• Have a strong interest in machine-learning and deep-learning, and primarily, MLOps and their engineering;
• 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 as well as operational capacity to setup and maintain DevOps/DataOps pipelines;
• Have knowledge of, or a willingness to familiarize themselves with, current research into machine learning for software, data ,and AI engineering;
• Have a commitment to develop algorithms that analyze Big Data from software-defined infrastructures as well as Big 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.

The Assistant Professor will be employed at Tilburg University.
We offer:

• A position as Assistant Professor for 32-40 hours a week (0,8-1,0fte) with a temporary contract for the duration of 12 (internal candidates) of 18 months (external candidates) with the option to get a fixed contract afterwards.
• The position comes with an attractive job package that features benefits including an attractive career trajectory, pension benefits, insurance discounts, ample vacation days (41), and a fixed end-of-year bonus (8,3%), to mention but a few.
• The gross salary is largely determined by the Dutch labour agreement (CAO NU) for universities, namely scale 11 (a maximum annual gross salary of €69.500,- )and we aim to offer a competitive salary within this framework. 
• Researchers from outside the Netherlands may qualify for a tax-free allowance equal to 30% of their taxable salary (the 30% tax regulation). The University will apply for such an allowance on their behalf;
• Assistance in finding accommodation (for foreign employees);
• The opportunity to perform cutting edge research in a large-scale joint data science project involving TiU, TU/e, JADS and a commercial partner and bringing together expertise of several senior researchers;
• Support for your personal development and career planning including participation in courses, summer schools, conference visits, research visits to other institutes (both academic and industrial), etc.;
• A broad package of fringe benefits (including excellent technical infrastructure, savings schemes and excellent sport facilities).

JADS

The Jheronimus Academy of Data Science (JADS) constitutes a unique concept in which an integrated approach to Data Science is created by combining the exact sciences of the Eindhoven University of Technology, with the social sciences of Tilburg University. JADS boasts three campuses at Tilburg, Eindhoven and ‘s Hertogenbosch. JADS Campus in ‘s Hertogenbosch revolves around research, education and valorisation on data entrepreneurship. 

More information about JADS can be found at www.jads.nl.