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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
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with a deep interest in the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a related field • Strong quantitative background
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science, statistics, machine learning, or related quantitative field. • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods
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, deep learning, or statistical modeling. Demonstrated experience working with clinical, digital health, or related biomedical data. Proficiency in Python, R, or other scientific programming languages