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multiple hospitals to ease the ingestion by the predictive models. Expertise in machine learning (ML) and deep learning (DL) is also valuable. The datasets may consist of 2D, 3D and 4D images from X-ray, US
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plan • Development of machine learning models for the classification of in vivo Raman spectra, applying chemometric methods. • Simulations and modification of data, advanced data analysis • Carrying out
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regulatory matters is a great advantage for the position. Important tasks of the work plan • Development of machine learning models for the classification of in vivo Raman spectra, applying chemometric methods
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impact the lives of hundreds of thousands (soon millions!) of people through personalized interventions to the right person at the right time. The machine learning effort is part of the Data Science team
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work with Prof. M. Ángeles Serrano and Prof. Marián Boguñá at the interface between Network Science and Machine Learning. The goal is to merge the best of the two worlds to produce a new generation of
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different areas of nanoscience and nanotechnology. Job Title: Junior Machine Learning Engineer Research area or group: Research Support Facilities Description of Group/Project: The machine learning engineer
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from in vivo Raman spectra • Applying chemometrics methods to machine learning models • Simulations and modification of data • Carrying out Raman measurements in vitro and in vivo • Development
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to machine learning models • Simulations and modification of data • Carrying out Raman measurements in vitro and in vivo • Development of protocols for biocompatibility and strict compliance with regulations
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machine learning offer a great opportunity to effectively extract evidence that will need to be calibrated in the form of a LR for presentation in court. Some members of the network, including the Ph. D
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Intelligent Systems, in particular, fuzzy systems, evolutionary algorithms, edge computing, tinyML, deep learning applied to computer vision, and data science and big data with Apache Spark. LanguagesENGLISH