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these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine
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reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you will work in the plasmalab team in the Faculty of Science and Engineering
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts
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of transverse transport on heat and mass transfer in a thermal arc plasma reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you
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experiments as well as bioinformatics and advanced imaging techniques. Your core tasks are: Cloning and expressing recombinant proteins. Developing and optimizing purification protocols. Designing and
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the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam generation unit, imaging lenses
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three main phases. In the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam
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are currently seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful
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continue reading! Join Us! Our modern society relies upon numerous electronic devices that use encryption to communicate and operate securely. However, even strong cryptography can break when the device
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will be determined in collaboration with you based on your strengths and interests, but could for instance involve developing new techniques for efficiently optimizing quantum computations, both in