You will join the
CaRe-NLP: Human-Centric and Responsible NLP methods for Dutch healthcare project. CaRe-NLP's main goal is to develop human-centric and responsible NLP and ML methods for healthcare in the Netherlands, Europe, and worldwide. CaRe-NLP's focus is methodological, meaning you will focus on developing, building, and testing state-of-the-art large language models (LLMs) that are interpretable and explainable, ensure privacy and fairness, prevent bias, and cope with data scarcity.
This PhD project will be co-supervised by dr. Iacer Calixto
and prof. Ameen Abu-Hanna at the University of Amsterdam and together with prof. Barbara Plank from the MaiNLP research lab at LMU Munich.
You will tackle relevant clinical problems and develop methods for non-English (including Dutch) multi-modal electronic heath records (EHRs) data that include (combinations of) free-text clinical notes collected in primary and/or secondary settings (including intensive care); medical images; time series measurements; medical knowledge graphs.
We currently offer the
PhD position titled
PhD-quantifying-disagreement-and-uncertainty where you will be responsible for developing, building and testing clinical LLMs that model uncertainty and disagreement in annotations (input) and predictions (output). You will develop solutions and apply them to learning from patient electronic health records (EHRs) and free text.
Furthermore, you will:
- Liaise with a network of clinical partners of the CaRe-NLP project and will tackle relevant healthcare problems using rich real-world clinical data;
- Have access to excellent HPC facilities and strong support to publish the results of your work in the best scientific conferences and journals in NLP, ML, (medical) AI, and healthcare in general;
- Contribute to the mentoring of master's students on topics related to your research.