The Department of Mathematics and Computer Science at the University of Southern Denmark for the Computational Biology group chaired by Associate Professor Richard Röttger invites applications for a postdoctoral position for the creation of a federated metadata repository amenable to federated machine learning for sensitive clinical data to be filled as soon as possible. The position will initially be for a period of one year, extendable up to three years. Application deadline: 25 April 2022.

A large roadblock of medical research is the difficult access to sensitive data which therefore hinders the training of complex and powerful machine learning concepts. This issue is amplified when considering rare diseases with low incidence numbers per hospital. The aim is to utilize the scattered data across Europe and make these data treasures amenable for machine learning.

First and foremost, this requires a federated metadata infrastructure which makes the scattered data findable and ensures interoperability, while not transferring any sensitive data from the site of storage. The federated metadata repository will allow the identification and selection of suitable patients across the sites of storage without the need of ever transferring sensitive information. Federated algorithms can subsequently be trained on the defined cohorts, again without sensitive data leaving the safe harbour of storage. Additionally, it is required to ensure the compatibility and interoperability of the data at the different sites by developing complex data homogenization and standardization pipelines which can flexibly be deployed and adjusted to the requirements of the data holding sites.

The successful candidate will be part of a large European endeavour Screen4Care and working in a dynamic, international, and interdisciplinary environment. Screen4Care is funded by the Innovative Medicines Initiative in a public/private partnership between numerous, high-profile research institutes and the EFPIA. The overall vision of Screen4Care is to shorten the path to rare disease diagnosis; the envisioned federated algorithms and infrastructure are one key aspect of fulfilling this vision.

Within SDU, the candidate will be embedded in a highly international and powerful consortium as a member of the Computational Biology group which offers a wide expertise in machine learning of biomedical data, both in the realm of unsupervised and supervised learning. We also provide the candidate with direct access to state-of-the-art computing facilities optimized for deep learning and distributed computing.

We are seeking outstanding candidates with strong analytical and problem solving skills, who are strong in written and oral communication (in English), and have documented experience in the development and maintenance of computer infrastructures and data homogenization, state-of-the-art web-development frameworks and virtualization techniques. Experience with working with clinical data and in machine learning are highly welcome.

Place of work:
Computational Biology Group (Associate Professor Richard Röttger, [email protected]), Department of Mathematics and Computer Science, located at the main campus of the University of Southern Denmark, Odense, Denmark.


Application, salary etc.
The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary and taxation.

The application must include the following:
1. Letter of motivation, including details on qualifications within subject area (max. one page).
2. Curriculum vitae, including information on previous employment, list of programming skills mastered by the applicant, and teaching and supervision experience.
3. A list of publications stating the scientific publication(s) on which the applicant wishes to rely (if available).
4. A suggested research plan, addressing the challenges described in the project .
5. A certified copy of your PhD degree certificate
6. At least one letter of recommendation from supervisors or previous employers. Should your referees wish to send their letters directly to us, please have them use e-mail: [email protected] mentioning your name and the title of the position in the subject line. And please note that these also need to reach us before deadline.

Shortlisting may be used in the assessment process.

Incomplete applications and applications received after the deadline will neither be considered nor evaluated.

To qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Applications must be submitted electronically using the link "Apply online". Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb. We strongly recommend that you read How to apply before you apply.

Further information for international applicants about entering and working in Denmark.