Postdoc: Bayesian Digital Twin for Implantable Device Performance

Delft University of Technology; Delft; On-site; EUR 41,000 - 64,000; Full time

Benefits offered by this job

ABP pension

Flexible working week

Leave hours buy/sell

Job summary

Delft University of Technology in Delft invites applications for a Postdoc position focusing on Bayesian methods to predict the performance of implantable medical devices. You will work on bridging studies, integrating prior knowledge with real-world data, and addressing regulatory evidence needs.

The role involves building a Digital Twin framework, collaborating across Europe, and contributing to the COMPASS4MD project.

Qualifications

• A methodologically oriented PhD degree e.g. in Epidemiology, Health Sciences, (Technical) Medicine, Medical Statistics, Data Science, Safety Science, Biomedical Engineering or a related field.
• Demonstrated experience in Bayesian inference / networks;
• Excellent research, academic writing and presentation skills, demonstrated by journal and / or conference publications;
• The ability to work both independently and as part of a team;
• High level of proficiency in English; Knowldege of Dutch language is optional but preferred;
• Experience with collaborative research projects is desirable.

Responsibilities

• Develop a methodology for bridging studies using Bayesian methods to integrate prior knowledge with real-world evidence.
• Transform static models into a "Digital Twin" for safety of medical devices and support regulatory decisions.
• Evaluate the quality of evidence after a device is on the market and provide a roadmap for regulators.

Skills

Bayesian inference

Bayesian networks

Statistics

Probability theory

Academic writing

Presentation skills

Teamwork

English proficiency

Education

PhD in Epidemiology/Health Sciences/Medical Statistics/Data Science/Safety Science/Biomedical Engineering

Job description

Delft University of Technology in Delft invites applications for a Postdoc position focusing on Bayesian methods to predict the performance of implantable medical devices. You will work on bridging studies, integrating prior knowledge with real-world data, and addressing regulatory evidence needs.

The role involves building a Digital Twin framework, collaborating across Europe, and contributing to the COMPASS4MD project.