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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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algorithms, integrate multi-modal physiological data to generate innovative body and muscle fitness parameters Manage documentation, preparing reports and publications, and ensuring effective communication
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the collection, processing, and analysis of physiological data from recreational and elite athletes across various exercise protocols. Utilizing machine learning and deep learning algorithms, integrate multi-modal
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with expertise in biology, biotechnology, computer science, microscopy and bio-engineering that is developing new microscopy hardware and new computational algorithms for the encoding and decoding
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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/validate algorithms for medical images and perform data analysis using state-of-the-art software programming tools such as Python. They are also expected to write publications, liaise with collaborators