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Fundació Privada Institut d'Investigació Oncològica de Vall d'Hebron (VHIO) | Spain | about 1 month ago
. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network
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models. Familiarity with cloud computing environments (AWS, Azure) and AI, machine learning, or NLP tools applied to biomedical data analysis. LanguagesENGLISHLevelExcellent LanguagesCATALANLevelExcellent
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integration of the project webpage into the institutional platform Uso de machine learning para estimar propiedades geomecánicas del terreno a partir de datos de laboratorio/ Use of machine learning to estimate
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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working model that combines remote working with work on-site, according to organizational needs and the nature of the tasks involved. About the UOC A leader in e-learning, our pioneering university is a
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FieldBiological sciencesEducation LevelPhD or equivalent Specific Requirements PhD in Physics, Computational Biology, Bioinformatics, or equivalent. Knowledge of biophysics, statistical physics, machine learning
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statistics (regression methods, time series analysis, multivariate analysis, clustering methods), machine learning techniques (neural networks, random forests, decision trees, SVMs, etc.) and optimisation
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. Preliminary exposure to machine/deep learning, statistical modelling or generative AI. Application process: Interested candidates are invited to apply via the PHYNEST online platform by submitting a full CV, a
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scalable and efficient software and firmware analysis methodologies using tools like Frida or IDA Pro, enhanced with traffic monitoring techniques and Machine Learning to detect and analyze vulnerabilities
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Requirements Educational Requirements: Artificial Intelligence. Deep Learning. Computer vision. Reasoning methods based on first-order logic. Design of complex computer systems. Professional Experience: In LLM