Postdoc in statistics to develop Bayesian privacy metrics for synthetic health data (2024-224-05725)

The Postdoc position

There is a large potential for using artificial intelligence(AI) for improving diagnosis, prognosis, and treatment of many diseases. Large amounts of clinical data are needed to train useful AI systems. However, patient data are person-sensitive and only select individuals can obtain access, which can be a huge roadblock for researchers and students. Many promising methods based on generative AI have been suggested to generate synthetic data, but we lack consensus methods for assessing synthetic data’s compliance to GDPR. The purpose of the position is to build such privacy metrics based on Bayesian statistics and apply them in several real-world settings of important clinical relevance. The postdoc will be responsible for developing the area with a group consisting of a PhD student, a data scientist, students, and a student helper.

The project is a part of the ambitious Novo Nordisk Foundation Data Science Collaborative Programme,“Synthetic health data: ethical development and deployment via deep learning approaches(SE3D)” which is a collaboration between Head of Center and Professor Martin Bøgsted, Center for Clinical Data Science, Aalborg University, Professor Anders Krogh and Data Scientist Jennifer Bartell, Center for Health Data Science, University of Copenhagen, and Professor Jan Trzaskowski, Department of Law, Aalborg University who are responsible for, respectively, developing privacy metrics, developing generative AI workflows, and ensuring GDPR compliance of the developed methods. There will also be interaction with the Novo Nordisk Foundation Data Science Infrastructure Programme,“the National Health Data Science Sandbox”, a network of data scientists and researchers across five Danish universities building training and research infrastructure.  

You may obtain further professional information from Head of Center, Professor Martin Bøgsted,[email protected] , tel.+45 5092 5639 or Group Leader, Assistant Professor, Charles Vesteghem,[email protected] , tel.+45.6166 7681.

Qualification requirements: 

You should hold a PhD degree in computer science, statistics, physics, mathematics, engineering, or a field of science relating to data science with emphasis on statistical methodological development. You are expected to have:

• Experience with Bayesian statistical modelling
• Strong programming skills in one of the main languages

It will be a plus, if the candidate has experience with one or more of these additional criteria:

• Synthetic data generation
• Machine learning
• Large health register data
• GDPR compliance rules
• Python
• Linux

Valued personal competencies are:

• Independent and creative
• Outgoing and enjoy providing advice within your field of expertise
• Proficient in English
• Flexible and interested in taking on different task

The application must contain the following:

• A motivated text wherein the reasons for applying, qualifications in relation to the position, and intentions and visions for the position are stated.
• A current curriculum vitae.
• Copies of relevant diplomas(Master of Science and PhD). On request you could be asked for an official English translation.
• Scientific qualifications. A complete list of publications must be attached with an indication of the works the applicant wishes to be considered. You may attach up to 5 publications.
• Dissemination qualifications, including participation on committees or boards, participation in organisations and the like.
• Additional qualifications in relation to the position. References/recommendations.
• Personal data.

The applications are only to be submitted online by using the"Apply online" button below.

Shortlisting will be applied. After the review of any objections regarding the assessment committee, the head of department, with assistance from the chair of the assessment committee, selects the candidates to be assessed. All applicants will be informed as to whether they will advance to assessment or not.

AAU wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background or belief.

For further information concerning the application procedure please contact Annette Sønderby Nielsen by mail [email protected] or phone(+45) 99408385.  Information regarding guidelines, ministerial circular in force and procedures can be seenhere.  

Employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities(the Appointment Order) and the Ministry of Finance's current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.