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supervision of Thaleia Dimitra Doudali. The specific topic of the research will be determined based on the common interests of the candidate and the supervisor. Here are some potential topics: [Machine Learning
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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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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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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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the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will learn how to produce CAR-T
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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
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Skills/Qualifications Academic background: Bachelor's Degree in Telecommunication Engineering, Computer Engineering, Biomedical Engineering, Industrial Engineering, Aeronautical Engineering or other
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Skills/Qualifications Academic background: Bachelor's Degree in Telecommunication Engineering, Computer Engineering, Biomedical Engineering, Industrial Engineering, Aeronautical Engineering or other