Postdoc Bayesian Methodology for Predicting the Performance of New Implantable Medical Devices

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

Unleashing the potential of Bayesian statistics to predict the performance of new implantable medical devices based on existing data while accounting for uncertainties

Postdoc Bayesian Methodology for Predicting the Performance of New Implantable Medical Devices

Job description

Innovative medical devices can offer important benefits to patients and are approved based on sufficient clinical evidence showing the safety and beneficial effects. Manufacturers currently face challenges in determining whether new clinical evidence is needed for a small change in the material or design, or that evidence is sufficient. In addition, regulators and notified bodies need to decide whether this requires a full (new) assessment of the evidence or can be considered an equivalent device. The key question for both stakeholders is whether we may expect that the performance is similar to that of the parent design, or that performance is uncertain and we need further evidence, but are lacking tools to inform their decision making for such device iterations.

This postdoc position will delve into these complexitieis by developing a methodology for bridging studies, using Bayesian methodology to integrate prior knowledge (historical data, benchmark tests, and literature) about exisiting meical devices with real-world evidence to predict the impact of iterative design changes on the device performance, accounting for the inherent uncertainties around such predictions.

A major challenge in assessing the performance of a medical device variants is lack of data for the new device variants. The postdoc will develop a mechanism to make use of existing data, translate past success into current confidence while satisfying medical device regulation requirements. It will transform the current static models into a \"Digital Twin\" for safety of medical devices, specifically supporting decisions regarding iterative small changes. Finally, the postdoc will evaluate the quality of evidence required after a device is on the market, and provides a roadmap for regulators to demand the right data at the right time, rather than merely more data.

The position is part of the European COMPASS4MD project, an EU funded project within the Horizon Europe programme.

The position is part of an international consortium and will involve close collaboration with research institutes, regulators, clinical experts, patient representatives, and other partners across Europe. You will contribute to joint project activities, exchange findings with partners from different countries and disciplines. The position therefore suits someone who communicates easily, enjoys working with people from different countries and disciplines, and is willing to take an active role in an international consortium. You should be comfortable working independently on your own research while also contributing to shared activities, meetings, workshops, and deliverables with European project partners. Some travel within Europe may be part of the position.

English proficiency is required. Proficiency in Dutch is considered an advantage, but is not a requirement. Experience with advanced statistical methods, econometric methods, and Monte Carlo simulation is an advantage. We do not expect candidates to already possess expertise in these areas; we particularly value the ability and motivation to work across disciplinary boundaries.

Job requirements

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. As the project combines quantitative analysis of clinical evidence with empirical research into regulatory decision-making, we particularly welcome candidates who demonstrate expertise in advanced quantitative methods to answer biomedical or clinical research questions or to tackle methodological problems in medical applications.

Specific requirements:

• Demonstrated experience in Bayesian inference / networks;
• Familiarity with statistics and probability theories;
• 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.

TU Delft (Delft University of Technology)

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty Technology, Policy & Management

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

Conditions of employment

• Duration of contract is 3 years. Temporary.
• A job of 36-40 hours per week.
• Salary range: €3706 - €5760.
• FTE: 1,0.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Expected starting date is January 1st 2027.

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.