PhD position in (Deep) Reinforcement Learning for Vocational Choice Tests

Vocational choice tests, in their current state, often fall short in delivering personalized and engaging recommendations, resulting in a lack of support during crucial choice moments at school. As a result, students rely heavily on parental advice, potentially limiting later career satisfaction. This research project aims to harness advanced machine learning techniques, such as (deep) reinforcement learning (RL), to offer tailored and improved vocational recommendations considering the individual student's interests.

Recommender systems can be used to match specific vocations or career options to the user, based on the user profile and the characteristics of the vocational choice options. Leveraging the ability of deep learning (DL), deep reinforcement learning (DRL) can be applied in large action spaces, such as vocational choice tests. On the downside, because they use DL, deep RL algorithms and systems are less explainable than conventional RL systems, thereby potentially creating a black-box system.

The primary objective of this PhD project is to design and develop recommender systems that employ innovative algorithms to deliver personalized vocational guidance. By incorporating sophisticated machine learning, we aspire to create a user-centric approach that considers individual interests and preferences. Resulting matches have to be explainable to the user. Therefore, in this PhD project the black-box of DRL algorithms will be opened, for example through simultaneous explanation and policy learning.

Moreover, we aim to integrate feedback mechanisms that allow users to shape and refine their recommendations further. This innovative approach not only enhances the usability of vocational tests but also empowers individuals to make better career choices.

The main research goals are:

1. Designing and implementing explainable (deep) reinforcement learning algorithms for recommender systems. 2. Evaluating algorithm performance through (1) user opinions on the recommendations, (2) user opinions on the vocational choice test itself, and (3) long term satisfaction and relevance of recommendations (validity).

Your profile

We look for a highly motivated, enthusiastic researcher who is driven by curiosity and has/is:

Master's degree or equivalent in Psychometrics, Statistics, Data Science, Artificial Intelligence or a related field;

Affinity and/or experience research in the social sciences (and conducting research involving human participants);

(Strong) programming skills with experience in machine learning and reinforcement learning being a plus.

A good team spirit and like to work in an interdisciplinary and internationally oriented environment;

Able to conduct independent research and willing to develop writing and publication skills;

Possess good communication skills and an excellent command of English.

Our offer

We encourage high responsibility and independence, while collaborating with colleagues, researchers, other university staff and partners. We follow the terms of employment by the Dutch Collective Labour Agreement for Universities (CAO). Our offer contains: a fulltime 4-year PhD position with a qualifier in the first year; excellent mentorship in a stimulating research environment with excellent facilities; and a personal development program within the Twente Graduate School. It also includes:

Gross monthly salary of € 2.770 in the first year, increasing each year up to € 3.539 in the fourth year;

Excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;

29 holidays per year in case of full-time employment;

A training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;

A green campus with free access to sports facilities and an international scientific community;

A family-friendly institution that offers parental leave (both paid and unpaid);

A full status as an employee at the UT, including pension, health care benefits and good secondary conditions are part of our collective labour agreement CAO-NU for Dutch universities.

Information and application

Are you interested to be part of our team? Please submit your application before 1 December 2023 and include:

A cover letter (maximum 2 pages A4), emphasizing your specific interest, qualifications, and motivations to apply for this position;

A Curriculum Vitae, including a list of all courses attended and grades obtained, and, if applicable, a list of publications and references;

Additional information can be acquired via email from Johannes Steinrücke ([email protected]).

About the department

The CoDE section consists of teachers and researchers with backgrounds in psychology, educational science, mathematics, or computer science. We teach courses on methodology, data-analysis, and cognitive psychology. Our research focuses on data-based solutions for societal problems related to education, health, and human factors. In our teaching and research we make use of the latest developments in measurement and (large-scale) assessment, such as neurophysiology, process data, extended reality, eye-tracking, psychometrics, and machine learning.

CoDE is part of the Department Learning, Data Analytics and Technology (LDT).

About the organisation

The Faculty of Behavioral, Management and Social sciences (BMS) aims to play a key role in understanding, jointly developing and evaluating innovations in society. Technological developments are the engine of innovation. As a technical university that puts people first, we tailor them to human needs and behavior and use social engineering to integrate them into society. We also ensure adequate governance at public and private level, and robust, inclusive and fair organizational structures. We do this by developing, sharing and applying high-quality knowledge in Psychology, Business Administration, Public Administration, Communication Sciences, Philosophy, Educational Sciences and Health Sciences. Our research and education in these disciplines revolves around tackling and solving societal challenges. The research programs of BMS are closely linked to the research of the UT institutes Mesa+ Institute for Nanotechnology, TechMed Center and Digital Society Institute.

As an employer, the Faculty of BMS offers work that matters. We equip you to create new possibilities for yourself and for our society. With us, you will become part of a leading technical university with increasing, positive social impact. We offer an open, inclusive and entrepreneurial atmosphere, in which we encourage you to make healthy choices, for example through our flexible, adaptable benefits.

Want to know more? Steinrücke, J. (Johannes)

Assistant Professor

Steinrücke, J. (Johannes)

Assistant Professor

Do you have questions about this vacancy? Then you can contact Johannes for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.

Contact

Phone:+31534897625

Email:[email protected]

How to apply Step 1

Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.

Step 2

Selection. The selection committee will review your application and you will receive a response within 2 weeks after the vacancy has been closed.

Step 3

1st interview. The 1st (online or in person) meeting serves as an introduction where we introduce ourselves to you and you to us. You may be asked to give a short presentation. This will be further explained in the invitation.

Step 4

2nd interview. In the second interview, we will further discuss the job content, your skills and your talents.

Step 5

The offer. If the conversations are positive, you will be made a suitable offer.

Your Colleagues

Berg, S.M. van den (Stéphanie)

Personal page

Velde, M.E. van der (Max)

Personal page

Hang, H. (Hanyuan)

Personal page

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Our university is a public institution that serves society. We are accountable to society for the ways in which we use our academic freedom. We are responsible for ensuring that the power of science and technology is harnessed to achieve the best possible impact in a changing world. We cherish our rich tradition of combining technical and social sciences in our five profiling themes: Improving healthcare by personalized technologies; Creating intelligent manufacturing systems; Shaping our world with smart materials; Engineering our digital society; and Engineering for a resilient world.

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We want our communities to flourish and show resilience, so we seize opportunities for innovation. We are knowledgeable and have an eye for what society needs. Our students and staff receive all the guidance they need in their quest for ecological, social and economic sustainability. “The University of Twente is all about people. Our sustainable technologies help to strengthen society.”

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