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proficiency in deep learning frameworks (PyTorch) is required. Prior experience or strong theoretical knowledge in active learning, multimodal deep learning, diffusion models, or representation learning
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proficiency in deep learning frameworks (PyTorch) is required. Prior experience or strong theoretical knowledge in active learning, multimodal deep learning, diffusion models, or representation learning
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detection and monitoring, invariant and distributionally robust representation learning algorithms, and deployment-time calibration with uncertainty quantification using approaches such as conformal
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team of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g
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other sources of noise. This motivates research in signal processing, temporal machine learning, representation learning, adaptation, and real-time inference. A second challenge is that neuromotor
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available in our group to work on the development, implementation, and application of hyper-efficient unsupervised learning techniques to chemical problems, with emphasis on improvements to representation
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, inductive biases in model architectures, hybrid simulation learning loops, or loss formulations that encode physical consistency. The work combines forecasting, representation learning, and scenario
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representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform theoretical advances into
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and mechanisms of democratic representation — with primary responsibility for the lab's partnerships, fundraising, and public communications. The Director will work at the intersection of math, law
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. The successful candidate will have Proven knowledge of soil science, fire ecology, and reed ecology Proven knowledge of data analysis and programming (R applications or comparable programming languages