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metal dichalcogenides are promising platforms for next-generation quantum and electronic devices, where atomic defects play a crucial role in determining functionality. This project develops a machine
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, with applications ranging from scientific research to medical imaging and marketing analysis. With the ever increasing amount of learning data, these algorithms face computational challenges
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factor: Experience in the experimental development of cellular biomimetic environments, namely in the breast cancer context, with non-neoplastic and neoplastic cells, in 2D and 3D culture (spheroids and/or
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, Matlab and/or R. Strong background in statistical analysis, applicable to experimental validation. Previous participation in scientific and/or technological research projects, preferably related to optics
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of bioinformatics tools, analysis of high-throughput sequencing data, and an interest in the field of ancient DNA (please provide details in the motivation letter and curriculum vitae). Workplan and objectives to be
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction