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in developing bioinformatics pipelines (Python/R/Bash) for genomic (NGS) and medical imaging data analysis, implementing artificial intelligence and deep learning techniques. - Experience in developing
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Experience in programming, expertise in software for handling big data, with a special emphasis on deep learning methods, and especially language models. 30% Complementary Training Having knowledge of software
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and paleosols 3) train and test deep learning algorithms. You will be required to take responsibility for all the steps involved in the “Phytolith analysis” work package of DEMODRIVERS. This will
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep
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regulated training activities and contribute to continuous training activities. Conduct research that allows the development of new AI methodologies based on deep learning that allow for assisting musical
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multi-omics data and the use of machine learning and data science techniques. Strong publications record according to his/her career stage. Skills: Excellent programming and scripting skills, with deep
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to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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programming (Python, MATLAB), neural networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm
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the LAMP group at the Computer Vision Center (CVC), in Barcelona, Spain. The position is for 2-3 years and linked to the project “Foundations for Adaptive and Generalizable Deep Learning” (EXPLORA