Two Postdoc positions in AI-based medical and life science data analysis

Research in collaboration with medical doctors for patient data analysis using machine learning has a high impact on public health for the vision of Digitalization in Health Care. Medical care givers such as doctors and nurses need to take important decisions based on observed patient data. Often the data is complex. Therefore, our objective is to use machine learning for assisting the decision of medical caregivers. We show two concrete examples as postdoc projects:

How to predict and detect an infection before visible symptoms like fever? When infections start, body parameters like breathing pattern, oxygen content, heart rate, pulses, etc. start changing. Then, can we track the body parameters and predict the infection buildup? If we can, then it saves time for medical intervention much before visible symptoms.
Medical doctors often face difficulty to choose a set of medicines from many options available for a patient. Medication is expected to be disease-specific as well as person-specific. Individual patients may respond differently to the same medication, so the selection of medication should be personalized to everyone’s needs and medical history. The question is: how AI can help doctors to identify existing medications and/or therapies that can be repurposed for the treatment of a disease? In this scope, we work with dementia patients.

In this project the postdocs will collaborate with doctors at world-renowned Karolinska Institute and Hospital. In addition, the postdocs will develop new AI / machine learning methods for life science data analysis, such as gene regulatory networks and metabolism networks. This will be in collaboration with SciLifeLab at Stockholm.