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(Python, Pytorch, Matlab...). A general interest in health and biology is welcome. Practical information The post-doc will take place within the Inria Morpheme team, a joint research group between Inria
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auto-encoder, back-propagation, • knowledge of R (main programming language), Python and C++. Application Application files should contain a resumé, an application letter and grade records of the 2 last
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. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted to clinical applications. ➢ A good knowledge of Python
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, clustering, classification • deep learning, variational auto-encoder, back-propagation, • knowledge of R (main programming language), Python and C++. Application: Application files should contain a resumé, an
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. Experience or good knowledge of analyzing other types of biological data. Knowledge of Python. Experience in leading research projects. Other expected qualities: Teamwork skills. Strong collaboration skills
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software development, with a focus on full-stack development Technical Skills Strong proficiency in Python 3 Flask/Django or other MVC framework HTML/CSS/JavaScript Experience with modern JavaScript
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background in one of the following areas: Statistical Physics Applied Mathematics Statistics & Bayesian Inference Proficiency in Python is also expected. Contacts dbc-epi-recrutement at pasteur dot fr
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should be proficient in Python, PyTorch or Scikit-learn. The candidate should also be endowed with a strong passion for multidisciplinary studies and all aspects of research ranging from fundamental work
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master’s degree in mathematics, physics or informatics with a strong knowledge in machine learning. Skills: Coding in Python and/or R is required. Previous knowledge in archaeology and zoo-archaeology would
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. Specific: Processing and analysis of 360° video images, expertise in Deep Learning – experience with Python (TensorFlow, PyTorch, Yolo), Git and Matlab. Processing of medical signals (ECG and respiratory