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building automated systems or ML pipelines – 15% Demonstrated experience implementing structured, scalable, or automated software systems. Evidence of experience with neural networks, LLMs, or training
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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and peritoneal carcinomatosis on MRI. State-of-the-art convolutional neural networks (e.g., U-Net–based architectures) will be trained and validated to achieve accurate and reproducible volumetric
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to work in. Research groups: Computational Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science
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Howard Hughes Medical Institute - Janelia Research Campus | Virginia Beach, Virginia | United States | 16 days ago
skills in Python and PyTorch are required, along with the ability to reason about neural network behavior from first principles. We seek candidates who can think critically about model design, understand
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, or materials informatics. Familiarity with explainable AI or counterfactual explanation methods. Experience with molecular dynamics data, graph neural networks, or multi-component system modelling. Track record
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this relationship impacts neural integrity in health and disease. Our ultimate goal is to identify new therapeutic strategies for neurodegenerative diseases. About Us We work at the interface
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. Recent advances in Deep Learning [LeCun2005] make it possible to study approaches based on neural networks to solve complex problems. These networks are resource intensive, often making them difficult
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recordings, behavioral training, and visual experimentation, while also developing and testing deep neural network models of visual representation. In short: experiments first, models second. Current and
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about neural network behavior from first principles. The role also requires knowledge of microscopy data formats and tools such as Zarr and Neuroglancer. We seek candidates who can think critically about