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Field
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Quantum computing is an emerging
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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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algorithms for very high speed coherent passive optical networks (VHSP) Implementation of DSP algorithms in MATLAB/C++, that can be used for ASIC development Development of our DSP software tools Research work
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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-modal data. * Develop and implement algorithms to process, clean, and transform large datasets to support research objectives. * Conduct exploratory data analysis, hypothesis testing, and develop data
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machine learning algorithms, conducting computationally intensive statistical analyses, summarizing research findings, and editing research papers. In addition to working closely with faculty, senior
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred