PhD Position Trustworthy Recommender Systems

Job description

Recommender systems are pivotal in shaping our online experiences, influencing the content we engage with, the products we purchase, and our social interactions. These systems, driven by machine learning, support a wide range of human decision-making processes across e-commerce, social platforms, entertainment, transportation networks, healthcare services, and cybersecurity.

While traditionally evaluated by their accuracy, there's a growing recognition within the research community of the importance of broader evaluation metrics. Fairness, diversity, robustness, explainability, transparency, and privacy are now seen as essential pillars for the overall health and sustainability of these systems. Trustworthy recommender systems are those that not only provide accurate and relevant recommendations but also prioritize these principles to foster user trust and confidence.

We invite prospective PhD candidates to engage in cutting-edge research focused on the development, evaluation, and enhancement of trustworthy recommender systems. Candidates will explore various aspects of trustworthiness, including but not limited to:

• Algorithmic Transparency and Explainability: Investigating methods to transparently explain the rationale behind recommendations, providing users with insights into why certain suggestions are made.
• Bias Mitigation and Fairness: Implementing strategies to address algorithmic biases, ensuring equitable treatment of all users and promoting diversity and inclusivity in recommendations.
• Privacy-Preserving Recommendations: Exploring approaches for personalized recommendations while preserving user privacy and minimizing data exposure.
• Robustness and Safety: Developing mechanisms to withstand adversarial attacks, ensure system stability in diverse environments, and protect users from harmful or inappropriate recommendations.

We offer a unique opportunity for PhD candidates to join our dynamic team and contribute to the forefront of recommender system research. As part of our team, you will delve into the fascinating realm of machine learning, exploring novel algorithms and methodologies to enhance the effectiveness, fairness, explainability, robustness, and privacy of recommender systems. Your work will shape the future of online experiences and have real-world impacts across various domains, from e-commerce and entertainment to healthcare and cybersecurity.

Requirements

Prospective PhD candidates should meet the following criteria:

• Hold a Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field.
• Demonstrate a strong mathematical foundation in optimization, statistical learning, and probability.
• Possess a thorough understanding of machine learning, information retrieval, and recommender system methodologies.
• Exhibit proficiency in programming languages, preferably Python, and in implementing machine learning solutions using PyTorch or TensorFlow.
• Display proficient communication skills in English, both written and verbal.
• Showcase the ability to work independently as well as collaboratively within a team.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the .

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

T he TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution . Flexible work schedules can be arranged.

For international applicants, TU Delft has the . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a for partners and they organise events to expand your (social) network.

Why Join Us?

• Impactful Research: Contribute to projects that make a significant difference in various sectors.
• Inclusive Environment: Work in a supportive and diverse setting that values every team member.
• Professional Growth: Engage in continuous learning and development opportunities.
• Collaborative Team: Join a team that encourages innovation and values collaborative efforts

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core  and we actively  to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click  to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

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