PhD position on Continuous Machine Learning for Adaptive Inspection Process (1.0 FTE)

Join our exciting research project as PhD candidate at Utrecht University and become part of the research collaboration AI4Oversight lab which is part of the Innovation Center for Artificial Intelligence (ICAI) . 
The Dutch government inspectorates play a critical role in safeguarding public interests such as food safety, a clean environment, fair working conditions or quality of education. To ensure effective supervision with a limited capacity at strategic and operational level, inspectorates need to work in a data-driven way and embed AI technology in their primary processes. The amount of information is too large and complex to be fully covered by human resources. At the same time, society rightly expects AI to be used in a responsible manner.
With joining the AI4Oversight ICAI lab, you join a community that collaborates to address AI challenges specific to the inspection domain leading to scientifically attested methods. The AI4Oversight lab connects the Human Environment and Transport Inspectorate (ILT), the Netherlands Labour Authority (NLA), the Inspectorate of Education (IvhO), Netherlands Food and Consumer Product Safety Authority (NVWA), Netherlands Organisation for Applied Scientific Research (TNO), Utrecht University and Leiden University. Collaboration between these organisations is seen as an essential element of our lab. Working together allows not only to develop new knowledge, but also to use each other’s expertise, to experiment together, to learn from each other and to bring theory to practice.
The execution of the research will be highly participatory. You will spend time at the offices of funding partners and have the opportunity to dive into the practical challenges and way of working of the partners. You will work together with data scientists of the practical partners, who will contribute with practical experiences and use cases. The AI4Oversight Lab hosts at least 6 PhD students and knowledge exchanges will be held regularly to promote collaboration. We are currently recruiting for 3 PhD positions simultaneously for this lab. We invite you to also check out the other interesting vacancies .
In this PhD position you will focus on enabling adaptive inspection methods with scientifically attested methods. Machine learning methods strongly depend on the completeness and representativeness of data to obtain high quality models suitable for supporting the inspectors in a responsible way. Typically, datasets have been selected with prior information and are limited in size. Moreover, the inspectees change their behaviour over time, partially influenced by the way of working of the inspectors. The challenge is to obtain effective models based on limited potentially biased data, while being able to adapt to trends and emerging behaviour. 
Key responsibilities:

• Conduct original and novel research in the field of active and on-line learning to efficiently learn models;
• Publish and present scientific articles at international journals and conferences;
• Collaborate with other PhD candidates in the AI4Oversight lab, researchers at the partners’ data science labs, the intended users and other stakeholders.

You are equipped with a critical mindset and motivated to use your experience in education and research to make a valuable contribution to pioneering research in the field of applied artificial intelligence. Next to that we would like you to bring:

• a MSc degree in Artificial Intelligence, Data Science, Applied Mathematics, Computer Science, or in a related field;
• good programming skills, preferably in Python;
• solid experience with machine learning, preferably in active learning and learning in non-stationary environments;
• excellent written and oral communication skills in English. Dutch proficiency or willingness to learn is a plus;
• ability to work with diverse stakeholders, e.g., industry professionals, academic researchers.

As we are selecting multiple positions for this research lab, we may request to consider your application for another research track. We will contact you if we do so.

We offer:

• a position for 4 years;
• a full-time gross salary ranging from €2,770 to €3,539 in scale P;
• 8% holiday bonus and 8.3% end-of-year bonus;
• a pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.

In addition to the employment conditions from the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. These include agreements on professional development , leave arrangements, sports and cultural schemes and you get discounts on software and other IT products. We also give you the opportunity to expand your terms of employment through the Employment Conditions Selection Model. This is how we encourage you to grow.
For more information, please visit working at Utrecht University .

As Utrecht University, we want to be a home for everyone. We value staff with diverse backgrounds, perspectives and identities, including cultural, religious or ethnic background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute.
If you are enthusiastic about this position, just apply via the "Apply" button. Please enclose:

• your letter of motivation, as separate PDF file, named [Your Family Name]_Coverletter.pdf;
• your curriculum vitae, as separate PDF file, named [Your Family Name]_CV.pdf;
• a copy of your Master's diploma and transcripts, as PDF file(s), again with your family name as prefix and a suffix indicative of the type of degree/transcript (e.g., Master, Bachelor);
• a copy of your Master's thesis, as PDF file named [Your Family Name]_Thesis.pdf;
• if you have accepted or submitted publications, state this in the letter of motivation and list them with bibliographic information (including DOI) in the CV;
• in the CV, state the names, affiliation, telephone numbers, and email addresses of at least two referees who have agreed to be contacted.

Some connections are fundamental – Be one of them
#FundamentalConnection