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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
conditions are particularly vulnerable, as their habitats with optimal environmental conditions become increasingly scarce. All in all, these ongoing changes highlight the urgent need to rethink the management
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the optimization and development of new protocols and applications; Prior experience with rodent experimentation, with a Function A / FELASA B certification or equivalent; Experience in services-oriented functions
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with privacy by developing techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student
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optimize the overall productivity and performance of Biostatistics staff and establishes and ensures the visions and goals of Biostatistics are in-line with the corporate goals; communicates the visions and
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. Job description Job responsibilities include engineering, transducing, and characterizing primary T cells with synthetic genetic circuits; optimizing and executing protocols for retroviral or lentiviral
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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-driven AI approaches, we strive to deliver the cost-optimized solutions for development of materials with ultrahigh-temperature stability, high specific strength and structure-function integration through
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exchange and interaction state of the art computing infrastructure (HPC) salary assigned according to the pay scale UKF standard social benefits, e.g. UKF job ticket UKF Your tasks: develop and optimize
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for industrial production focusing on Tenebrio and black soldier fly. The tasks will include: Establishing nutrient requirements for optimal production and resource utilization in insects produced at an industrial
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on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend