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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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aspects of photonics. Research is performed within nanophotonics, photonic nanotechnology, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed optical transmission systems, and
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enable the development of fault-tolerant quantum computing hardware and quantum algorithms that solve life-science-relevant chemical and biological problems. Within NQCP we are currently pursuing several
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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to have experience with: Phase equilibrium calculation algorithms and their integration into CO2 capture simulation Thermodynamic modeling of phase equilibrium and thermophysical properties related to CO2
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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the Department of Immunology and Microbiology, Faculty of Health and Medical Sciences. This role involves developing and applying advanced bioinformatics algorithms to investigate the functional diversity
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of precision medicine by developing innovative statistical genetics methods, implementing state-of-the-art machine learning algorithms, and integrating artificial intelligence to uncover novel biological
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16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Monterey, CA, USA, 2019, pp. 199-207, doi: 10.1109/MASS.2019.00032. Responsibilities and qualifications As a Postdoc at DTU