Postdoctoral Researcher ​/ AI & Scientific Software Engineer – Autonomous Live-Cell Microscopy a[

Postdoctoral Researcher / AI & Scientific Software Engineer – Autonomous Live-Cell Microscopy and Laboratory Automation

As a leading research institution for microbial biotechnology, the Institute of Bio- and Geosciences – Biotechnology (IBG-1) focuses on molecular and applied microbiology. Interdisciplinary teams are developing biotechnological processes for tomorrow’s industry, with a focus on increasingly automated and miniaturised experiments.

We are looking for a highly motivated researcher to develop novel machine learning and computer vision methods for autonomous live-cell microscopy, intelligent experiment control, and scientific workflows. Join an interdisciplinary team at the interface of AI, microbiology, and laboratory automation to shape the future of data-driven live-cell analysis.

Microorganisms in the gut microbiome play a key role in health and disease, yet their behavior in complex and dynamic microenvironments remains poorly understood. Within a Helmholtz collaboration, we are developing a high-throughput single-cell analysis platform that combines microfluidics, advanced live-cell microscopy, and AI-based image analysis to study microbial consortia. You will drive the development of the next generation of image analysis, scientific software, and intelligent experiment control for microfluidic live-cell analytics in close collaboration with experimental partners at HZI, Helmholtz Munich, and HHU.

• Develop machine-learning–based workflows and scientific software for segmentation, species classification, and lineage tracking in multi-species time-lapse microscopy data
• Optimize models and analysis pipelines for real-time performance, enabling adaptive imaging and feedback control
• Design active-learning and retraining strategies to robustly generalize to new microbial communities
• Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition
• Build scalable, maintainable, and open-source software for high-throughput image analysis and laboratory automation

You will present your results at international conferences, publish in leading peer-reviewed journals, and contribute to the supervision and training of students within the consortium.

• Excellent Master in Computer Science, Engineering, Biophysics, Applied Mathematics, Computational Biology, or a related discipline
• Proven programming expertise in Python (scientific Python, PyTorch) with solid experience in scientific computing, reproducible software development, and modern software engineering practices; familiarity with C++, Linux, and high-performance computing is an advantage
• Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
• Experience in one or more of the following areas: object detection and segmentation, multi-object tracking, time-series analysis, probabilistic modeling and uncertainty quantification, real-time or streaming data processing, or multimodal learning
• Strong mathematical and statistical background, combined with excellent analytical and problem-solving skills
• Interest in developing AI methods at the interface of biology, robotics, and laboratory automation, with enthusiasm for collaborating closely with experimental scientists. Prior wet-lab experience is welcome but not required
• Excellent communication and collaboration skills, with enthusiasm for working in an international and highly interdisciplinary research environment
• A demonstrated research track record through publications, open-source software contributions, internships, thesis projects, or comparable scientific achievements
• Excellent command of English; knowledge of German is an advantage but not required

We work on highly topical, socially relevant issues and offer you the opportunity to actively shape change! You can expect a wide range of opportunities:

• Meaningful tasks: An exciting, interdisciplinary research environment at the interface of AI, imaging, microbiome research, and laboratory automation within a Helmholtz-wide…