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pathomics dedicated to personalized medicine. This innovative and rich approach stems from the explanatory integration of deep learning in computational histopathology as well as spatial transcriptomics
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the development of models that enable robots to autonomously execute these activities and generalize across different environments. The goal of the position is to bridge this gap by learning robotic policies
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interface (restorative BCI), consist in providing real-time feedback to a patient about his or her own brain activity in order to learn how self-regulate specific brain regions and help him or her perform a
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. To make deep learning algorithms efficient in real life it is important to combine software and hardware optimization when creating new deep learning algorithms. During the PhD we plan to propose novel
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within a Research Infrastructure? No Offer Description Contexte et atouts du poste The main goal of this PhD project is to develope a deep learning framework for the design of cyclic peptides. This project
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of Inria and will be supervised by Nikolaos Georgantas ([email protected] ) and Maroua Bahri ([email protected] ). Mission confiée Automated Machine Learning (AutoML) is an approach
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cluster computer system to realize big-data analysis and simulations. Mission confiée Context of the project Artificial Intelligence (AI) and especially Deep Learning (DL) have undergone many successes in
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facial expressions and modifications in speech patterns using NLP and machine learning techniques. This will be achieved by analyzing video recordings of multiple patients, with each recording annotated by
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. Supervised learning is one of the main branches in Artificial Intelligence (AI). Training a model requires an ensemble of data to train on. Each data item is associated with a label, which is the best
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, still energy efficient. Compétences Required technical skills: Good knowledge of computer architectures and embedded systems Machine Learning (pytorch/tensorflow) HW design: VHDL/Verilog basics, HW