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partners. Qualifications Ph.D. in Computer Science, Applied Mathematics, or a related field. Strong publication record in machine learning, with preference for expertise in representation learning, deep
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.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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at a reduced cost. In this context, we are looking for a highly motivated postdoctoral researcher to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and
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deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress