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This PhD project is part of an NWO-funded KiC project: ‘Responsible Scaling of Data-driven Approaches for Enhancing Mental Healthcare’. You will collaborate with UMC Utrecht, as well as external partners including InfoSupport, E-health academy, Diabetesfonds, mental health institutes, MIND, and De Nederlandse GGZ. The Social and Affective Computing group conducts research into multimodal analysis of human behaviour and affect, and in responsible ways of computer-based analysis in mental healthcare.
As a PhD candidate you will develop responsible algorithms (fair, explainable and privacy preserving) to address clinical treatment questions such as those related to depression, mental health and diabetes.
In this project, we will use both structured and unstructured data from the clinical health records of (adult) patients stored in the e-health modules. By applying machine learning techniques in a federated, explainable and fair manner, we aim to responsibly identify patient profiles during different stages of the treatment trajectory that are associated with responses to specific treatment choices. The outcome is the development of novel, responsible algorithms and models that provide insights into which treatments produce what results for which patients.
Our work in the Social and Affective Computing group is highly interdisciplinary. In the affective computing domain, we collaborate intensively with academics and practitioners as well as institutions in psychology, psychiatry, and linguistics. In the social computing domain this ranges from sociology to international law and politics. This PhD position is the result of both political (e.g., the recently approved EU AI law), social and technological developments that require accountability, fairness and transparency of critical algorithms.
We are looking for collaborative candidates who have:
We value candidates with a strong interest in research in affective computing.
Gender balance specifically, and diversity in a broader sense are very important to the Department. Hence, we encourage applications from women and individuals from diverse backgrounds.
We offer:
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