What you do This unique tenure track position offers the best of both worlds: 50% of your work will be performed from the Campus The Hague of the LUMC, and the other 50% from the Leiden Institute of Advanced Computer Science (LIACS) within the faculty of Science of Leiden University. This means that you will be a strategic linking pin in various collaborations at the junction of data science and natural language processing in the broad area of population health. This position is embedded within the recently launched Population Health Living Lab (PHLL) The Hague, which allows you to contribute to a sustainable and robust realization of the most extensive population dataset within the Netherlands, and to consequently perform novel multidisciplinary data analyses. As assistant professor, you are expected to contribute to at least one of our overarching research themes on our Translational Data Science research agenda. Regarding teaching, you are expected to contribute around 50% of your appointment to LUMC’s Population Health Management (PHM) master’s program and LIACS’s curricula, which includes co-developing, co-teaching, and coordinating the data science courses as well as the track itself, as well as thesis supervision. Highlights- You position yourself as an interorganizational linking pin in the Medical Delta ecosystem at the junction of Data Science initiatives in the broad area of Population Health
- You contribute to the further development of the Population Health Living Lab (PHLL) ecosystem with respect to research related to data engineering and translational data science
- You contribute to the Population Health Management master’s program by co-developing, co-teaching and coordinating data science courses as well as the track itself
What we ask You’re an expert in either the research theme of Data Engineering/Information Science or (Big) Data Analytics/Machine Learning, and knowledgeable in the other one. Similarly, you are an expert in utilizing statistical methods and machine learning techniques on real data. You are conscientious and creative, and you have experience at the postdoctoral level with a strong publication record and a proven track record in teaching. Furthermore, you are experienced in raising research funds. You are passionate about investigating and utilizing data science technologies, focusing on state-of-the-art application-oriented research in Explainable AI, AutoML, Big sensors/wearables data, speech recognition, neuro-linguistic programming, affective computing, etc. You are skilled in Python development, like using SciKit-Learn, HuggingFace, PySyft, and Streamlit. Lastly, you are communicatively skilled and you work well collaboratively.
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