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The Climate Policy Lab (CPL) at the Center for International Environment and Resource Policy (CIERP), The Fletcher School, Tufts University, is seeking a Postdoctoral Scholar for the academic year 2026-2027
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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on machine and deep learning methods for analyzing the heterogeneity of microbiota and inferring activities of biological pathways. The Institute provides an international and interdisciplinary research
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. • Contribute to interdisciplinary research projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Create a Job Match for
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, tissue sections, RNA/DNA, tabular data) for predictive modelling using software such as Python Documented experience of neural networks, image processing, deep learning algorithms, and data visualization
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at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim
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communication signals on our mental processes. What you will do Build novel deep learning architectures for auditory prediction (speech and/or music) prioritizing explainability and cognitive hierarchies Quantify