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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object
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. Expertise and knowledge in AI deep learning model development on histology whole slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 1 day ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by
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bioinformatics, deep learning and/or biomedical image and clinical data analysis (e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of single cell RNA-sequencing
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reconstruction - Estimation theory - computational methods and deep learning approaches. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7249-HERRIG-026/Default.aspx Work Location(s) Number
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Description The Deep Learning laboratory in the Division of Science, New York University Abu Dhabi, seeks to recruit a research assistant to work on Deep Reinforcement Learning (DRL). The successful
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advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. He/she will support the development of an improved forest RTM that can
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Experience with MATLAB/Simulink, including Control System Toolbox, System Identification Toolbox, or Deep Learning Toolbox. Understanding of battery systems, electrochemical energy storage, or battery
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deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in
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evaluate innovative methods based on generative models and Vision-Language Models. Design, implement, and validate deep learning approaches for vision applications. Publish research results in leading