Are you looking for a position in a highly multidisciplinary environment with excellent potential to create societal impact? If so, apply to this joint position of assistant professor Data Sciences in Population Health.
• 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
• 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 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.
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.
We offer a full-time tenure track appointment of six years, after which period this position may lead to a permanent appointment depending on good performance.
Leiden University requires teaching staff to obtain the University Teaching Qualification (UTQ). If the successful applicant does not already possess this qualification or its equivalent, they must be willing to obtain this qualification within two years.
For this position we will request at least three references.
Acquisition as a result of this vacancy is not appreciated.
Stories from our colleagues
Read stories from our colleagues here
50% of your integrated activities will be embedded, paid for and carried out at the LUMC The Hague, and 50% of the integrated activities will be embedded, paid for and carried out at LIACS in Leiden. At the LUMC Campus The Hague, you will contribute to the Population Health Living Lab The Hague, and substantially to the population health dataset in which multidisciplinary research across different faculties, with data science as one of the core disciplines, is conducted. At the computer science institute LIACS, you will be part of, and contribute substantially to, the artificial intelligence and data science focus area. You will collaborate with existing groups focusing on data science (Prof. Kraaij and Prof. Spruit), automatic machine learning (Prof. Hoos), natural and evolutionary computation (Prof. Bäck), and/or reinforcement learning (Prof. Plaat).
Your career at the LUMC
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