Postdoc Position in Medication-related Alert Recommender Systems

Postdoc Position in Medication-related Alert Recommender Systems

Too many alerts lead to alert fatigue and increase the risk of medication errors (ADEs). You will develop machine learning and neurosymbolic methods for personalized alerts that better match the situation and needs of healthcare providers.

The project

The high number of alerts presented to the user can lead to alert fatigue and contribute to clinician frustration and burnout. Ignoring clinically relevant information and non-adherence to alerts can raise severe ADE. Alert Recommendation Systems (ARSs) are novel systems that can provide personalized alerts that are more relevant and better fit care providers’ expertise and needs.

You will contribute to the solution to this problem by:

1. Building a proof-of-concept ARS for Amsterdam UMC's medication alerts to increase the overall alert acceptance.
2. Investigating the ARS potential value compared to the current CDSS alerts.

To achieve these goals, the candidate will explore the use and development of recommendation techniques based on machine learning, deep learning, and neurosymbolic AI to uncover potentially complex interactions between alert and patient data.

About your role

We are looking for a Postdoc candidate who is eager to contribute to better clinical decision support and safer medication prescription in the hospital settings with the help of ARS.

You will investigate how to build and evaluate a suitable ARS for Amsterdam UMC’s medication alerts. This investigation will address several methodological topics; a non-exhaustive list includes:

• Collaborative filtering;
• Content-based filtering;
• Hybrid recommender systems;
• Neurosymbolic recommender systems;
• Autoencoder-based recommender systems.

You will provide efficient and scalable implementations of your methods and will integrate them with popular open-source systems. Via the Department of Medical Informatics, you will have access to large datasets comprising millions of CDSS alerts.

About you

Prerequisites:

• PhD in computer science, machine learning, artificial intelligence, data science, medical informatics, or related fields;
• Hands-on experience in machine learning;
• Strong programming skills in Python and machine learning libraries (e.g., PyTorch, Sklearn);
• Creative and independent mindset;
• Capable of working in multidisciplinary environments;
• Fluency in English.

Not required, but helpful:

• Experience with recommender systems;
• Experience working with real-world (medical) data, e.g., having experience with data wrangling, analysis, visualizations, etc;
• Contribution to open-source projects;
• Willingness to learn Dutch.

Our offer

• A flying start to your career in scientific research.
• Plenty of room for your drive to shape tomorrow's healthcare.
• Working on large-scale and in-house research, with motivated colleagues from all over the world.
• You will be employed by Amsterdam UMC Research BV.
• A contract for 12 months.
• Salary scale 10: € 3.598 to € 5.669 gross based on full-time employment (depending on education and experience) and a year-end bonus of 8.3%.
• Holiday hours: 190,4 per year for fulltime and a possibility to save additional hours.
• Pension accrual with BeFrank, a modern, comprehensible and fairly priced pension.
• For >7 km each way, 100% reimbursement for public transport travel costs and, for private transport, €0.18 per km up to a maximum of 40 km each way.
• Do you prefer walking or cycling? Take advantage of our good bike scheme. Moreover, you will receive a reimbursement of €0.18 per km.

About your workplace

You will be appointed at the Medical Informatics department, a vibrant community of talented researchers, with whom you will have the opportunity to interact. You will also have the opportunity to contribute to top-rated education programs.

You will be supervised by Dr. Iacopo Vagliano and Prof. Ameen Abu-Hanna. Dr. Vagliano is Assistant Professor of Artificial Intelligence and Health Data Science and works in the area of medical artificial intelligence, including health recommender systems, multimodal machine learning, deep learning, and neurosymbolic AI, notably combining structured clinical variables, unstructured clinical text and knowledge graphs. Prof. Abu-Hanna is a Principal Investigator in Methodology in Medical Informatics and has extensive experience in AI, ML, prognostic & causal modelling, and their statistical and clinical evaluation.

Amsterdam UMC Research BV supports non-profit scientific research. In doing so, we provide researchers with everything they need to excel. Our principal investigators (PIs) and project leaders offer support in the field of project management, finance and human resources. In medical scientific research projects, legal support is also provided.

Amsterdam UMC has an open culture. This means that we hope that everyone feels welcome in our organization and that we strive to offer equal opportunities to everyone. We therefore cordially invite all interested parties to respond to this vacancy.

During the publication period, applications will be handled continuously. If the vacancy is filled, it will be closed prematurely.

If you have any questions about this position, please do not hesitate to contact Dr. Iacopo Vagliano, Assistant Professor of Artificial Intelligence and Health Data Science, at i.vagliano@amsterdamumc.nl.