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, implement, and scale AI-driven technologies in ways that make a true difference to society. Our ability to respond to the opportunities afforded to society will depend on training and building a workforce
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selectivity is the first important barrier to overcome in order to perform quantitative analyses for each pollutant and avoid ionic interference between the different sensors used in the project. Sensor
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protein expression in cells from tissues of women at high risk for cancer, and to identify differences in tumor responses to cancer therapies. Using biological knowledge, identify candidate cell
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optimization, using models to test the effectiveness of different courses of action. In addition, the Data Scientist 1 uses a variety of data mining and analysis methods, using a range of data tools, building
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credits per year (11-month type) and provides students with learning support services during the assigned period. Lecturers normally teach up to 3 different courses, with each section typically consisting
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and tools to develop IoT applications, to analyze and design IoT architectures for different application domains, and to develop data analytic tools to analyze the large amounts of data generated by
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algorithms for optimal operation of grid-integrated LDES; Develop a co-simulation framework to analyse LDES performance under different grid scenarios. Collaborate with consortium partners to translate
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cell-tracking algorithms, we can follow thousands of individual cells in real time as they respond to carefully designed chemical and mechanical cues. These approaches generate uniquely rich datasets
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techniques to several hundred local, national and international users annually. Specific tasks Develop and apply different image analysis approaches to, for example, segment, track, and characterize cellular
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a