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channels, transporters, and stress signaling systems. The project requires thorough knowledge of bacterial cell biology and molecular genetics as well as hands-on experience with cloning, live-cell
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and molecular genetics as well as hands-on experience with cloning, live-cell fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model
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of infancy, primary immunodeficiencies are now viewed as more common, also explaining disease in children, adolescents, and adults. With high-throughput genetics, rare, potentially disease-causing variants can
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and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product. The post-doc project is about extending the biomass algorithm to also include data
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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as
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evaluating efficient and scalable techniques for systems that process and answer such queries (e.g., query optimization algorithms, adaptive query processing approaches). Conducting this research work includes
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. This involves formulation, implementation, and validation of novel hybrid models. The study emphasizes methodological innovation, scalable algorithms, and translation to industrially relevant multiphase reactors
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this project, we will develop new algorithms and computational schemes as well as further develop existing computational frameworks in the team. We will focus on two related frameworks in the project
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Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms Who we are looking for The following requirements are mandatory: A