Intensive care units (ICUs), such as neonatal ICUs or surgical ICUs, are data-intensive environments, where intensivists must cope with a relentless flow of information to make fast and accurate decision. This information, ranging from vital signs, waveforms, demographics, test results,… needs to be combined and analyzed to make fast and accurate decisions on which patients’ life depends. In this project we will investigate if AI models can analyze this data and provide decision-making support.
What are you going to do?
As part of your PhD, you will develop new deep learning solutions for the analysis of different waveforms, such as blood pressure waves or thromboelastograms, to diagnose the current status of the patient, predict medical complications or conditions, and make decision about suitable treatments and actions. Specifically, you will address the challenges of creating robust decision-making algorithms with missing data and providing clinical-based interpretability of the obtained decisions.
You will be embedded in the qurAI group, an interfaculty, multidisciplinary group between the Institute of Informatics of the University of Amsterdam and the Department of Biomedical Engineering and Physics of the Amsterdam University Medical Center (AUMC). We focus on the development, validation and clinical integration of AI solutions for data analysis challenges in healthcare. The group aims at designing and enabling socially responsible AI innovations in healthcare.
You will work under the supervision of Prof. Clarisa Sánchez from the qurAI, who will also serve as your promotor. You will also work in close collaboration with Prof. Alexander Vlaar and his group at the department of Intensive Care Medicine of AUMC. The project is defined within the Research Priory Area (RPA) AI for health decision-making at UvA. This RPA aims at conducting interdisciplinary research regarding responsible AI-driven health decision-making by joining expertise from AI, ethics, law and medicine.
What do we require?
If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via this link. We will accept applications until 11 January 2022.
Applications in .pdf should include:
We will invite potential candidates for interviews within two weeks after the closing date.