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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 2 months ago
). - Artificial intelligence and machine learning. - Advanced programming in Python and use of machine learning/bioinformatics libraries. - Software development and database management. - Ability to work in
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(Machine Learning Force Fields, ML-FF) to simulate gas-phase fragmentation processes via molecular dynamics. Design and maintain a project-focused results database (schema, metadata, upload/retrieval scripts
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Fundació Privada Institut d'Investigació Oncològica de Vall d'Hebron (VHIO) | Spain | about 1 month ago
.), command-line tools (bwa, samtools, bedtools, etc.) and biological databases (cBioportal, COSMIC…). Fluency in R and/ or Python. Proficiency in English. Knowledge of statistical modelling or machine learning
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the medium and long term. We are looking for a Machine Learning Research Engineer: The ideal candidate will bring deep expertise in state-of-the-art deep learning methods applied to computer vision, 3D
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projects using NGS techniques applied to oncology. The candidate will mainly carry out the following tasks: • Analysis of high-throughput omics data with state of the art methods including machine learning
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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): Application of Machine Learning for the prediction of concrete properties. Design and performance of advanced tests on concrete. Implementation of multi-criteria models for the evaluation of sustainability and
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research institute at the University of Girona focused on computer vision and robotics. It combines fundamental and applied research in areas such as underwater robotics, medical image analysis, and
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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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statistics (regression methods, time series analysis, multivariate analysis, clustering methods), machine learning techniques (neural networks, random forests, decision trees, SVMs, etc.) and optimisation