Algorithmic hiring is on the rise and rapidly becoming necessary in some sectors, yet these systems run the risk of reproducing and amplifying discriminatory biases. FINDHR is an interdisciplinary EU project that seeks to prevent, detect, and mitigate discrimination in AI with a focus on the algorithmic hiring use-case. Through a context-sensitive, interdisciplinary approach, FINDHR will develop new technologies to measure discrimination risks, to create fairness-aware rankings and interventions, and to provide multi-stakeholder actionable interpretability.

At the University of Amsterdam, we are looking for a postdoctoral researcher or PhD candidate who is interested in designing and evaluating fairness-aware search algorithms. In contrast with fairness-aware ranking in contexts where click feedback is immediate, fairness-aware ranking for algorithmic hiring raises new challenges of learning from delayed rewards (i.e., was the candidate ultimately shortlisted, interviewed, hired?), leveraging complex feedback (e.g., expanded user models, long-term feedback loops), and supporting optional positive actions (i.e., affirmative action). The applicant will develop algorithms to meet these challenges and work with the interdisciplinary FINDHR team to develop a software guide, demonstration, and software package for fairness-aware ranking in the context of algorithmic hiring.

What are you going to do

Tasks and responsibilities

Postdoc:

• Create, evaluate, and describe fairness-aware learning to rank algorithms that learn from delayed rewards and complex feedback, including modelling of factors related to discrimination;
• Collaborate with project members to develop a guide and software package for fairness-aware ranking;
• Present research results at national and international conferences, workshops and journals;
• Become an active member of the research community and collaborate with other researchers, both within and outside the Informatics Institute;
• To show independence in achieving research goals and collaborating with PhD students and researchers;
• Assist in teaching activities, such as teaching labs and tutorials or supervising bachelor and master students.

PhD:

• Create, evaluate, and describe fairness-aware learning to rank algorithms that learn from delayed rewards and complex feedback, including modelling of factors related to discrimination;
• Collaborate with project members to develop a guide and software package for fairness-aware ranking;
• Present research results at national and international conferences, workshops and journals;
• Become an active member of the research community and collaborate with other researchers, both within and outside the Informatics Institute;
• Pursue and complete a PhD thesis within the appointed duration of four years.
• Assist in teaching activities, such as teaching labs and tutorials or supervising bachelor and master students.

Your experience and profile

Postdoc:

• A PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field;
• A thorough understanding of both information retrieval and machine learning;
• An interest in algorithm development and in their implications for people impacted by those algorithms;
• Solid programming skills with experience using Python and machine learning frameworks;
• A strong academic record and eagerness to tackle complex scientific problems;
• Have a record of publishing in relevant high-quality conferences or journals in the above fields.
• Be motivated and capable to coordinate and supervise research.
• The ability to work in multidisciplinary teams;
• A good knowledge of written and spoken English.

Proven experience in computer vision or machine learning is a big plus.

PhD:

• A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field;
• A thorough understanding of both information retrieval and machine learning;
• An interest in algorithm development and in their implications for people impacted by those algorithms;
• Solid programming skills with experience using Python and machine learning frameworks;
• A strong academic record and eagerness to tackle complex scientific problems;
• The ability to work in multidisciplinary teams;
• A good knowledge of written and spoken English.

Proven experience in computer vision or machine learning is a big plus.

For this project we are looking for either a postdoctoral researcher or a PhD candidate. Please indicate in your application which position you're interested in.

Postdoc:

We offer a temporary employment contract for 38 hours per week for a period of 34 months. The preferred starting date is as soon as possible.

The gross monthly salary, based on 38 hours per week and dependent on relevant work experience, ranges between € 2,960 to € 4,670 (scale 10). This does not include the 8% holiday allowance and the 8,3% year-end allowance the UvA offers. The UFO profile Researcher 4 is applicable. A favourable tax agreement, the '30% ruling', may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

PhD:
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is as soon as possible. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary, based on 38 hours per week, ranges between € 2,541 in the first year to € 3,247 in the last year (scale P). This does not include the 8% holiday allowance and the 8,3% year-end allowance the UvA offers. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the '30% ruling', may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Both positions:

Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:

• 232 holiday hours per year (based on fulltime);
• Multiple courses to follow from our Teaching and Learning Centre;
• A complete educational program for PhD students (not for the Postdoc position);
• Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
• 7 weeks birth leave (partner leave) with 100% salary;
• Partly paid parental leave;
• The possibility to set up a workplace at home;
• A pension at ABP for which UvA pays two third part of the contribution;
• The possibility to follow courses to learn Dutch;
• Help with housing for a studio or small apartment when you're moving from abroad.

Are you curious to read more about our extensive package of secondary employment benefits, take a look here.

Faculty of Science

The University of Amsterdam is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

The Information Retrieval Lab (IRLab) focuses on bringing the right information to the right people in a fair and transparent way. IRLab works on data-driven methods to understand content, to analyse and predict user behaviour and to make sense of context and information, all in the setting of search engines, recommender systems and conversational assistants. Applications are ubiquitous: tools to find documents on the web, recommend products, discover music and much more. IRLab positions itself in the AI and Data Science research themes of the Informatics Institute.