Phd Position Data-efficient Machine Learning for
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PhD Position Data-Efficient Machine Learning for Context-Sensitive Affective Computing-
**_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.).
- 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.
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.)
Conditions of employment
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.
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.
Challenge. Change. Impact
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (E
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