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. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model for diagnosis and prognosis of different sarcomas. He/she will develop and train
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efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 1 month ago
at the Centre Inria de l'Université de Lille in the Scool team. He or she will be in contact with experts of sequential decision making. The candidate will study different research questions related
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About the Role The position is funded through the EPSRC project “Zeros, Algorithms, and Correlation for graph polynomials”. We study various combinatorially defined polynomials such as the
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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isolation algorithms and data-driven classifiers. As postdoc, you will principally carry out research. You are expected to actively publish and present results in scientific journals and conferences. A
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performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven