PhD Candidate (m/f/d)

The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states.

At our location in Dortmund, we invite applications for the Research Group Analysis of Microscopic BIOMedical Images (AMBIOM):

PhD Candidate (m/f/d)

The position is part of the DFG-funded project: ComplexEye - a 96/384-well plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells.

You will be responsible for

• Developing new machine learning algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research
• Developing solutions to integrate large foundation models into microscopy image analysis and analytical data analysis workflows, together with other team members
• Building new foundation models for microscopy image analysis
• Implementing AI-based microscopy image analysis software as python packages
• Reporting findings and methods in conference and journal papers

Your profile

• Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science/biomedical engineering or of relevant scientific field
• A solid background in machine learning
• Extensive experience with either computer vision or image analysis
• Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi-modal large language models)
• Good presentation and writing skills
• Proactive, independent, and solution-oriented way of working
• Fluent English (spoken and written)
• Publications at top-tier computer vision conference or journals is a plus
• Experience with open-source software development is a plus

We offer

• A clear research topic as well as multifold training and support for PhD students in framework of ISAS and the Leibniz association
• Training and scientific development opportunities in an international environment and an excellent working atmosphere in a very dynamic and professional team
• Extensive state-of-the-art equipment and infrastructure in various analytical methods
• The opportunity to present your data on international conferences and participate in workshops
• A wide range of opportunities for further training and qualifications
• Flexible working times, mobile working and attractive social benefits
• Support in finding balance between work and family life (including finding childcare facilities, advice on caring for relatives) through a family service
• Workplace health promotion and support for participation in TU Dortmund University sports activities

The full-time position is offered for three years. The position is available immediately. The salary will be according to the German TV-L. The time limitation of the contract is based on the Wissenschaftszeitvertragsgesetz (WissZeitVG).

Non-residents who apply for this job will receive help from the institute to find accommodation and to handle authorities. Applications from disabled applicants are welcome. ISAS supports the principle of equal opportunity for all employees and therefore particularly encourages women to apply.

ISAS collects and processes the personal data of its applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at: .

The closing date for applications is February 26, 2026 . Please apply via our applicant portal . If you have any questions (reference number 388_2026), feel free to contact the Human Resources team ([email protected]). Further information about the institute can be found at: .