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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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-omics data sets generated with innovative high-throughput technologies used in Research Sections I and II (e.g. sensory, metabolome, proteome and transcriptome data) by using efficient algorithms and
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are developing algorithms and tools to address these bioimage analysis problems, which are all driven by real biomedical research. Depending on the background and interest, the student will have the opportunity
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-sampling data. Furthermore, the position holder will play a central role in creating high-quality training datasets (seagrass maps) to support artificial intelligence (AI) algorithms used in related projects
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for new quantum computing algorithms. It will rely on statistical structure learning represented by knowledge graphs and efficient low-rank tensor compressions. We are looking for: A completed scientific
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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solid understanding of data structures, algorithms and statistical methods. Collaborative and Solution-Oriented Approach: A strong interest in collaborating with research communities, understanding
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data Integration of data from multiple Omics experiments Your profile: You hold a university degree (master or PhD) in bioinformatics or computer science, with experience in algorithm and software