Challenge: Explore context-sensitivity of affect detection and data-efficient algorithms addresssing it.

Impact: Increased performance and robustness in real-world settings (e.g. healthcare).   

Job description
We seek a PhD student interested in working with us to explore the context-sensitivity of data-driven approaches for affect prediction from human behavior. In particular, we aim to empirically explore this challenge and develop data-efficient algorithms to address it. Modern intelligent systems are envisioned to collaborate closely with humans in complex task environments, such as health care or education. To support this enterprise, Affective Computing aims to enable such systems to dynamically understand and respond to humans' thoughts and feelings during interactions. One major challenge in achieving this goal is the strong context-dependence of emotional processes, which vary widely based on cultural, situational, and personal factors. Moreover, obtaining large amounts of training data for relevant settings might be difficult, e.g., due to privacy concerns or the complexity of obtaining viable ground truth. As a result, existing data-driven approaches still struggle to provide reliable affect estimates across different real-world settings.

In this project, you will explore how different context characteristics captured in training datasets influence the (1) generalizability and (2) data efficiency of multimodal machine learning approaches' for automatic affect prediction. Your task will include developing a suitable methodology for such an investigation. Depending on your chosen approach, this stage could also involve designing and collecting new datasets involving human participants. Building on the insights developed from this process, you will then focus on advancing data-efficient or robust machine-learning techniques (e.g., learning with privileged information or meta-learning) to better address relevant aspects of context sensitivity. On one hand, the project offers technical and empirical challenges, but there is also room for theoretical and conceptual work. This can be balanced and explored according to your interests.

Our research environment offers a dynamic, stimulating, and diverse atmosphere, providing you with opportunities to collaborate with experts in the field. You will work within the Intelligent Systems department's Pattern Recognition and Bioinformatics group. The group comprises labs with researchers working on diverse topics, such as machine learning, computer vision, and human-centered AI. It is very international and socially active. During the project, you will be advised by Dr. Bernd Dudzik (Human-oriented Machine Intelligence) and Dr. Tom Viering (Pattern Recognition).     

Requirements
A Master’s degree or equivalent (or about to graduate with one) in a relevant field (Artificial Intelligence, Computer Science, Data Science, Cognitive Science, etc.).

In addition, we are looking for candidates with the following essential qualifications:

• Experience with machine learning/deep learning and quantitative research methods through coursework or projects.
• Strong analytical and conceptual modeling competencies.
• Good programming skills (preferably Python), including ML methods and libraries.
• Excellent (written and verbal) proficiency in English.

We encourage you to apply even if you do not meet all the criteria above as long as you are willing to acquire the complementary skills.

Preferred optional qualifications:

• Experience with multimodal affective computing models or user-modeling techniques
• Experience in collecting multimodal datasets or running experiments with participants
• Experience with interdisciplinary research projects.
• Familiarity with different Theories of Emotion (e.g., Cognitive Appraisal Theories, Constructivist Theories, etc.)

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 Graduate Schools Admission Requirements.

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 values and we actively engage 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 here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

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 € 2872 per month in the first year to € 3670 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.

The 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 Coming to Delft Service. 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 Dual Career Programme for partners and they organise events to expand your (social) network.

Additional information
For more information about this vacancy, please contact Dr. Bernd Dudzik (b.j.w.dudzik@tudelft.nl).

Application procedure
Are you interested in this vacancy? Please apply before 30 October 2024 via the application button and upload:

• Motivation letter (max 2 pages) addressed to Bernd Dudzik. The motivation letter should summarize:

1. why you would like to do a PhD,
2. why you are interested in the project/topic,
3. why your profile is suitable for the job,
4. what you hope to gain from the position.

• CV (max 2 pages).
• Academic transcripts (both MSc and BSc degrees).

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Please do not contact us for unsolicited services.