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Field
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experience with algorithms relevant to computational biology documented programming skills, e.g. in Python and R very good communication and organizational skills with the ability to work to timelines, both
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a development. In the frame of a
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, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular
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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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international research environment covering a wide variety of research areas, such as algorithms and data structures, machine learning, computer graphics and vision, database systems, artificial intelligence
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral