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across disorders. Experience with multiple sequencing platforms including both short- and long-read sequencing is preferred. Bioinformatic approaches to identify targetable regions of the genome
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issues or areas of critical data examination. Works with statistics on defining and documenting programming endpoint algorithms across a study, drug program and/or contributing to TA level algorithms
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reliable algorithms for estimating the aforementioned parameters on a global scale will enable the implementation of operational services in precision agriculture and forest management. This PhD project will
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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of machines and structures in collaboration with other departments from Aarhus University and multiple industrial partners; including a world leader in sensing technology. In particular, the algorithm platform
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and