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interactions and translational vaccine design and prediction. The candidate has the option to choose different research methods such as machine learning, deep learning, natural language processing (NLP), and
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will have the opportunity to work on open hybrid dynamical systems to study and advance the work on switched networked systems, networked cyber-physical systems, and learning via graphical models
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. Super resolution imaging and blind/non-blind deconvolution using Tikhonov regularization / total variation Deep Learning approaches / UNet / GAN modelling for US,CBCT and H&E/IHC images SVD, matrix
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SLURM Proven track record of executing data science projects Ability to work effectively with a team of scientists and students Desired Qualifications* Experience with machine learning/deep learning and
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, development, testing, and implementation of machine learning tools to improve patient safety. Fellows will gain deep knowledge of R, Python, and other software tools to accomplish project aims.