The Social and Affective Computing group at the Utrecht University Department of Information and Computing Sciences is looking for a PhD candidate to conduct research on explainable and accountable affective computing for mental healthcare scenarios. The five-year position includes 70% research time and 30% teaching time. The post presents an excellent opportunity to develop an academic profile as a competent researcher and able teacher.

Affective computing has great potential for clinician support systems, but it needs to produce insightful, explainable, and accountable results. Cross-corpus and cross-task generalization of approaches, as well as efficient and effective ways of leveraging multimodality are some of the main challenges in the field. Furthermore, data are scarce, and class-imbalance is expected. While addressing these issues, precision needs to be complemented by interpretability. Potential investigation areas include for example depression, bipolar disorder, and dementia.

The PhD candidate is expected to bridge the research efforts in cross-corpus, cross-task multimodal affect recognition with explainable/accountable machine learning for the aim of efficient, effective and interpretable predictions on a data-scarce and sensitive target problem. The candidate is also expected to be involved in teaching activities within the department of Information and Computing Sciences. Teaching activities may include supporting senior teaching staff, conducting tutorials, and supervising student projects and theses. These activities will contribute to the development of the candidate's didactic skills.

We are looking for candidates with:

• a Master?s degree in computer science/engineering, mathematics, and/or fields related to the project focus;
• interest or experience with processing of audio/acoustics, vision/video or natural language;
• interest or experience with machine learning, affective computing, information fusion, multimodal interaction;
• demonstrable coding skills in high-level scripting languages such as MATLAB, python or R;
• excellent English oral and writing skills.

The ideal candidate should express a strong interest in research in affective computing and teaching within the ICS department. The Department finds gender balance specifically and diversity in a broader sense very important; therefore women are especially encouraged to apply. Applicants are encouraged to mention any personal circumstances that need to be taken into account in their evaluation, for example parental leave or military service.