Multimodal Health Data Researcher
4 days ago
We are seeking highly motivated individuals to join our team as a PhD student or postdoctoral researcher in the field of multimodal health data evaluation metrics. The successful candidate will work on developing novel methods to evaluate and increase the diversity of the evaluation data, design competitions with multiple metrics, and study how the novel design affects underrepresented groups in data science.
The project is funded by the Novo Nordisk Foundation Data Science Ascending Investigator grant titled "CHEETAH: CHallenges of Evaluating Teams and Algorithms." This project aims to hire 2 PhD students and 2 postdocs to work on various aspects of healthcare algorithm development, including chest x-ray imaging, NLP data, cardiovascular imaging, and tabular data.
Key responsibilities include:
- Developing novel machine learning methods for multimodal health data
- Evaluating and increasing the diversity of the evaluation data
- Designing competitions with multiple metrics and studying their impact on underrepresented groups
- Collaborating with the research team to achieve project goals
Required qualifications include a MSc degree in computer science, mathematics, cognitive science, human-computer interaction, or a related field, experience with programming in Python, and experience with machine learning for imaging and NLP data.
Acknowledging that even highly qualified applicants may not meet all requirements, we encourage applications from candidates who are interested in this project and have relevant skills and experience.
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