Bayesian Forecasting for Implantable Device Performance

Delft; Delft; On-site; EUR 42,000 - 54,000; Full time

Benefits offered by this job

Individual employment package

Pension ABP

Leave hours scheme

Education & training

Job summary

TU Delft invites applications for a postdoctoral position on Bayesian methodology to predict implantable medical device performance. The role integrates prior knowledge with real-world data to quantify uncertainty in design changes, supporting regulatory decisions and safety evaluations.

You will build a framework for bridging studies, transform models into a Digital Twin, and collaborate with Institutes, regulators and clinicians across Europe. English is mandatory; Dutch is a plus.

Qualifications

• PhD in a quantitative field with biomedical context.
• Experience with Bayesian methods and regulatory questions is valued.
• Strong writing and presentation skills, with publications.

Responsibilities

• Develop a Bayesian methodology for bridging studies and digital twin concepts.
• Collaborate with international partners, regulatory bodies and clinicians.
• Communicate findings through papers, meetings and deliverables; travel within Europe.

Skills

Bayesian inference

Statistics & probability

Academic writing

Independent & teamwork

English proficiency

Education

PhD in Epidemiology/Health Sciences/ Biomedical Engineering

Job description

TU Delft invites applications for a postdoctoral position on Bayesian methodology to predict implantable medical device performance. The role integrates prior knowledge with real-world data to quantify uncertainty in design changes, supporting regulatory decisions and safety evaluations.

You will build a framework for bridging studies, transform models into a Digital Twin, and collaborate with Institutes, regulators and clinicians across Europe. English is mandatory; Dutch is a plus.