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within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or a
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 30 days ago
develop our state-of-the-art imaging systems by optimizing the hardware and integrating real-time data processing and analysis through machine learning techniques to achieve precise characterization
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation
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Your Job: Combine multimodal brain imaging with advanced image-processing, data science, and AI techniques to perform image alignment, segmentation, and classification to construct and validate
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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collaborate closely with a dedicated team of soil fauna experts, ecological data modelers, computer-vision system engineers. Your Tasks Establish data science pipelines, data-modelling strategies, model
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of Schleswig-Holstein (10 %) and is one of the internationally leading institutions in the field of marine sciences. Through our research and our commitment to the transfer of knowledge and technology, we
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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves