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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based
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responsibility for carrying out research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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of research. Experience in method development, either quantum chemistry and/or nonadiabatic dynamics. Interest in extending methods that allow the application of quantum algorithms, using quantum
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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populations. Knowledge of real-time control algorithms for assistive or rehabilitation systems. Experience contributing to patent applications, translational research, or spin-out formation. Downloading a copy
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. Experience conducting or supporting user studies involving patients or vulnerable populations. 4. Knowledge of real-time control algorithms for assistive or rehabilitation systems. 5. Experience
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gene gain/loss events, horizontal gene transfer, and functional diversification within gene families. You will apply statistical models and machine learning algorithms to identify associations between
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and implementing vision processing algorithms that enable robust robot tracking and autonomy. The ideal candidate will possess hands-on experience designing, implementing, and deploying computer vision