316/2025 One PostDoc/PhD position and One PhD position

Vacancy Notice 316/2025

Otto von Guericke University Magdeburg (OVGU) is an internationally oriented and regionally networked university with a strong research profile.

The Faculty of Computer Science (FIN), Knowledge Management and Discovery Research Lab (KMD) seeks to fill the following two vacancies:

One PostDoc/PhD position and One PhD position (m/f/d) on multimodal learning in tabular temporal data

Salary scale:

13 TV-L

Date commencing:

Fixed term (until):

3 Y (+ up to 3 Y)

Contract status:

50% -100% each

We are a university with a focus on engineering and natural sciences as well as economics, human sciences and medicine. We offer excellent study and working conditions to 13,000 students from Germany and abroad as well as approx. 3,000 employees.

Who is KMD:

The Knowledge Management and Discovery team (KMD), Faculty of Computer Science in OVGU does research on sparse temporal data, foremostly in clinical and digital healthcare. We have a broad portfolio of methods - stream learners, active and semi-supervised learners for glassbox classifiers, pattern extractors from time series, and cost-awareness plugs. We work together with medical researchers and clinicians. Our mission is to help them make the best from data that are not traditionally used in clinical decision making, e.g. signal from wellness trackers and from low-end sensors. We are involved in interdisciplinary projects, including the TACTIC Graduate School at OVGU

) towards co-evolution in human-technology interfaces.

Position 1 (PostDoc/PhD):

Multimodal learning on biomedical, clinical or digital health time series, with emphasis on fusion and/or domain transfer, and on the integration of the learners in operative biomedical/clinical processes

Position 2 (PhD):

Multimodal learning on clinical or digital health time series, with emphasis on taking cost, energy, latency and other properties of sensors into account

Your profile as PostDoc candidate:

Masters degree and PhD in machine learning in the biomedical or clinical domain, familiarity with sensorics and time series analysis, proficiency in one or more of Python / R / Java, experience in teaching support. English proficiency is a must, German proficiency is an advantage.

Your profile as PhD candidate:

Master degree in AI or data science or computer science with emphasis on data science, very good degree grade, familiarity with sensorics and time series analysis, proficiency in one or more of Python / R / Java. Familiarity with biomedical or clinical applications is of advantage. English proficiency is a must, German proficiency is an advantage.

75% percentage:

This is a pair of two non-full positions, the default of each one is 75% funding. You can apply for a 50% funding, eg if you already hold a PhD grant and you want to top it up, or if you wish to work halftime only. If one position is occupied by a candidate who applied for a 50% funding, the other position will be topped to 100%. You cannot apply directly for a 100% funding.

Your tasks:

You expand and promote our research, you get involved in our interdisciplinary cooperations, propose topics for joint research, present research results and extend the KMD scientific network. You contribute to the KMD teaching (1 hour per week for each 25% of the position) by taking up exercises, by getting involved in seminars and student projects, by winning and co-supervising students and, for Postdoc position, by additionaly building up a course of yours in the domain of multimodal learning. You participate in grant proposals. You contribute to KMD self-administration, which includes exam preparation and correction, reporting, website management and public relations. If you are not yet proficient on German, you learn German to support in our German bachelor level courses.

What we offer:

You will become member of a multinational team working on the challenges of learning from sparse temporal data. We give you the opportunity to do research with our collaborators in medicine and healthcare, to get inspiration and data from them and to define new research agenda topics.

By joining our team, you will qualify yourself towards cutting edge temporal technologies for applications in healthcare, medical research and possibly also industrial research. The official qualification target for PhD positions is a PhD, and this involves research, teaching assistance and supervision of students. The official qualification target for Postdoc is habilitation, and this involves research, participation in grant proposals, teaching and supervision of students.

You will benefit from our structures and offerings in the fields of sustainability, diversity, family support and staff development. Our location in the center of a thriving, lively and family-friendly state capital guarantees a high quality of life and a wide range of leisure activities. For more information, please visit

and the KMD page

For further information about the position, please contact Prof. Myra Spiliopoulou at

You will benefit from our structures and offerings in the fields of sustainability, diversity, family support and staff development. Our location in the center of a thriving, lively and family-friendly state capital guarantees a high quality of life and a wide range of leisure activities. For more information, please visit

Otto von Guericke University Magdeburg is a signatory of the German Diversity Charter. We welcome your application, regardless of gender, cultural and social background, age or sexual orientation. Applications from severely disabled people or people with an equivalent impairment will be given priority in the case of equal suitability, ability and professional expertise. Otto von Guericke University Magdeburg strongly promotes gender equality in all professional areas.

Please note the information for storage of personal data:

Please send your complete application (motivation letter, curriculum vitae, graduation certificates, references) by January 06, 2026 using the online application portal.

Otto-von-Guericke-Universität Magdeburg

Dezernat Personalwesen