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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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development, including Python, model integration, and system architecture design. Excellent communication and leadership skills, with prior experience in mentoring students or leading small teams. PhD degree in
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research on human-AI interaction on social media. The ideal candidate will possess advanced knowledge of R and/or Python software, have experience performing statistical analyses on large datasets, have
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multilingual or speech impairment contexts. Programming Skills Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with web development (e.g., FastAPI, Flask
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statistical skills. 6. Facility working with analysis software. Desirable Qualifications: Computer programing in Matlab, Python, C/C++ or similar. Expertise in machine learning methods and applications
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solid Python skills. Interest in computer vision, representation learning, concept drift, Statistical Process Monitoring (SPC/SPM), active learning/DOE, MLOps. Curiosity, independence, and excellent
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beneficial Experience in working with mouse models Advanced programming skills in Python are beneficial Strong motivation and ability to work both independently and collaboratively as a member of
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annotation; proficiency in R or Python; and excellent English. Experience with spatial transcriptomics and immunology of autoimmune diseases is desirable. Interested candidates should send a motivation letter
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FieldEngineering » OtherEducation LevelBachelor Degree or equivalent Skills/Qualifications - Experiencia avanzada en lenguajes de programación de Servidores Web y clientes web (TypeScript, SQL, Python, R, Java
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related discipline. The role requires strong programming skills in Python, competency in data analysis and scientific computing, and the ability to work with large datasets. Familiarity with machine