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working atmosphere flexible and family-friendly working time model and the possibility of mobile working (up to 50% of working time) subsidy for a company ticket for public transport
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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and physics is curious, open-minded, a team player, and well organized has interest in modelling complex systems, ideally for particle radiation effects. Experience in these areas is therefore highly
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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of Europe’s biggest research centers and help us to shape change! Are you eager to pursue a four-year doctoral project that bridges scientific disciplines? Are you excited by complex societal challenges
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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complex transport systems: Perception: Developing robust models to handle noisy, complex spatiotemporal data, integrating physical constraints, and generalizing from limited labels. Decision: Designing
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interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
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. He/she/they will learn and apply state-of-the-art molecular and cell biology technologies established in our team, ranging from in vivo disease models to multi-omics and single cell analysis
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on uncovering mechanisms of CNS myelination and neuroinflammation. The lab combines advanced in vivo imaging approaches with complex models of demyelinating disease to investigate glial cell dynamics, immune-glia