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Field
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the research group Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational Chemistry, Systems Chemistry, and
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wide range of numerical and machine learning (ML) computer algorithms as applied to reservoir engineering and geophysical imaging. This includes the simulation of thermal-hydro-mechanical-chemical (THMC
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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. Optimizes and extends algorithms, analysis pipelines, and software in order to establish and ensure effectiveness and scalability of computing infrastructure. Provides consultation for and expertise with
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, implementation, and testing of a wide range of numerical and machine learning (ML) computer algorithms as applied to reservoir engineering and geophysical imaging. This includes the simulation of thermal-hydro
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data to generate mathematical models of cellular signaling dynamics. You will help design algorithms for data-driven model discovery, test proposed algorithms in computational simulations, and
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estadísticos para su integración en plataformas de datos. --------------------------- Design and development of statistical data analysis algorithms for integration into data platforms. Where to apply E-mail
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, manage your own academic and administrative activities, adapt existing and develop new robotic methodologies, design and implement algorithms, deploy and test on hardware platforms, and analyse data from
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: designing and developing prototype algorithms for ground processing of Synthetic Aperture Radar images, with a focus on X-band systems; developing Synthetic Aperture Radar image processing; validating and
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of quantum algorithms that can be successfully executed. To improve the computational capabilities of current quantum computers, crosstalk errors and decoherence of a quantum computer need to be characterized