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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | 22 days ago
. Test model predictions in behavioral experiments. Investigate how principles of biological adaptability can inform the design of efficient and robust learning algorithms for artificial systems
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executing the experiments Developing relevant algorithms for experimental data post-processing Mentor and work closely with multiple Ph.D. and M.S. students as well as four principal investigators from
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. The goal of these two postdoc positions is to contribute to the modelling, simulation, and optimization across different LDES technologies, from device (ESS+inverter) to system level (grid integration) under
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, reconstructing data testing different algorithms using multi slice algorithms, adapting ptychography reconstruction algorithms, stream lining the ptychographic data analysis: accelerating the reconstruction
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information about the university, please visit www.xjtlu.edu.cn . RESEARCH AREAS Currently, we are seeking candidates from different research areas. The more details can be kindly found as below: 1. Industrial
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different research areas. The more details can be kindly found as below: 1. Industrial AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making
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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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-exploiting optimization algorithms will be used to improve the performance of the numerical methods also for this class of problems. As postdoc, you will principally carry out research. A certain amount of
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analysis algorithms will be used to assess how different neutrophil subpopulations directly and indirectly kill tumour cells, and how this behaviour is influenced by other cells in the tumor microenvironment
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of AI for the integration of multimodal healthcare data specifically incorporating patient preferences. This includes investigating new methods but also designing and benchmarking integration algorithms