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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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and image analysis within the project, responsible for designing and iterating on machine learning architectures, managing training pipelines and datasets, and optimizing models for deployment across
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models are deeply rooted in real-world biological data. The collaborative approach allows for the development of predictive models that bridge the gap between theory and experiment, with a focus on high
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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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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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1 Apr 2026 Job Information Organisation/Company La Rochelle Université Research Field Computer science Environmental science Computer science » Modelling tools Computer science » Programming
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking a highly motivated Postdoctoral
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gained to improve the sustainability of agriculture and the climate change resilience of crops. The Maere lab at PSB ( http://www.maerelab.be ) is active in the fields of computational biology
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The research fellow will focus on foundation model-based world model development for embodied intelligence, and
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gained to improve the sustainability of agriculture and the climate change resilience of crops. The Maere lab at PSB (http://www.maerelab.be ) is active in the fields of computational biology, evolutionary