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- UNIVERSIDAD POLITECNICA DE MADRID
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Field
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scientific programming in Python and the use of frameworks such as PyTorch or TensorFlow. It is also necessary to have experience in federated learning and deep learning applied to medical imaging, as
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: Biochemistry Microbiome ecology Metabolic modelling Python and/or R Microbiome bioinformatics Longitudinal or temporal data analysis Microbial ecology and community dynamics This profile would suit someone with
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empirical data You have experience setting up Nextflow pipelines You have experience working in high-performance computing environments You have programming competence in R and/or Python Desirable but not
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empirical data You have experience setting up Nextflow pipelines You have experience working in high-performance computing environments You have programming competence in R and/or Python Desirable but not
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, parabolic equations, ray-tracing. Skills: excellent computational skills: Python, Fortran, HPC. Language skills: Fluent in English, Spanish is not required but advantageous. Specific Requirements We
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/Qualifications - Programación en Python - Manejo de herramientas de análisis de datos - Experiencia en herramientas de simulación de redes satelitales - Experiencia en análisis de datos Specific Requirements
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or equivalent Skills/Qualifications - Conocimientos demostrables de Python, Matlab, SageMath y MySQL. Nivel avanzado Specific Requirements - Máster en matemáticas y/o ingeniería computacional - Doctorado en
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academic fields are encouraged to apply. High proficiency in written and oral English. Specific Requirements Good and demonstrable programming skills, preferably in Python (e.g. personal projects, software
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Good and demonstrable programming skills, preferably in Python (e.g. personal projects, software development experience, etc.). A high level achievement and experience in multi-disciplinary collaboration
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analysis (FEA) and numerical modelling, preferably using Abaqus. Good programming skills, preferably in Python. Ability to work effectively both independently and as part of a multidisciplinary research team