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development of methods to detect synthetic nucleotides using the Oxford Nanopore platform. The postdoc will be part of the Microbial Metagenomics group with 15 researchers at various career levels with
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performance, and preventing failures like fires or explosions. Current prediction methods mainly rely on extensive lab testing and modeling, using insights from destructive post-mortem analyses to improve
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competencies The ideal applicant profile should demonstrate expertise in one or more of the following areas: optimization algorithms (heuristics, metaheuristics, exact methods), learning-based approaches
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with 15 researchers at various career levels with expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center
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scale. Furthermore, the work will include biomass extraction and fractionation using novel green extraction methods as well as detailed biomass chemical characterization using spectrophotometric bioassays
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. The Postdoc will conduct research on methods to enhance the performance, safety, and lifetime of lithium-ion batteries by integrating physics-based modeling with data-driven approaches. The work will include
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applications. The project investigates two complementary reuse strategies: Repurposing of large blade segments into structural elements (e.g., beams, panels) Material recycling of shredded fibers for use as
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paralleling SiC MOSFETs and power modules and must have experience with hardware methods to attenuate the oscillations successfully. Your experimental experience must be relevant to the tasks and obtained from
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learning on graphs, including knowledge graphs, social and biological networks, financial networks, temporal and dynamic graphs, uncertain graphs, explainability and fairness of deep learning methods
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to join our team working on next-generation speech enhancement technologies. The project explores innovative approaches that move beyond traditional reference-based methods, leveraging optimal transport and