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 algorithms. 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, e.g., synthetic data that can be safely shared in support of exploratory analysis, model prototyping, and IT infrastructure development. However, we lack consensus methods for assessing generative AI’s compliance to GDPR. The purpose of the position is to build Bayesian metrics for privacy preserving AI(e.g., synthetic data generation, federated learning, and privacy aware algorithms) and apply them in several real-world settings of important clinical relevance. The Postdoc will be responsible for leading the development of Bayesian metrics for privacy preserving AI for synthetic data and attracting further funding to the field of privacy preserving AI with a group consisting of students, a data scientist, and a PhD student.
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 Project Manager 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.
There will be limited teaching and supervision responsibilities primarily in clinical data science at the Faculty of Medicine, but also in other study programmes at the University.
You may obtain further professional information from Head of Center, Professor Martin Bøgsted, [email protected], tel.+45 5092 5639.
Qualification requirements:
Appointment as Postdoc presupposes scientific qualifications at PhD–level or similar scientific qualifications.
Your background is in statistics, computer science, mathematics, engineering, or a field relating to data science with emphasis on statistical modelling. You are required to have:
- Experience with statistical modelling
- Strong programming skills in one of the main languages(e.g., R or Python)
- Proficient in English
It is an advantage, if the candidate has experience with one or more of these additional criteria:
- Synthetic data generation
- Privacy preserving AI
- Machine learning
- Large health register data
- GDPR compliance rules
- Valued personal competencies are:
- Independent and creative
- Outgoing and enjoy providing advice within your field of expertise
- Flexible and interested in taking on different tasks
The research potentiel of each applicant will be emphasized in the overall assessment.
The application
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.
- 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 [email protected] or phone(+45) 9940 8385. Information regarding guidelines, ministerial circular in force and procedures can be seenhere.
Wages and employment
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.
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