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Division, New York University Abu Dhabi, seeks to recruit a post-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and
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high throughput cellular assays. Perform statistical analysis and proficiently use graphing software or R scripts. Successful Candidates Will Have: Experience in analysis of protein kinases
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Multi-modal Machine Learning—including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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position focuses on advancing the integration of gene regulatory network (GRN) simulations into multicellular and tissue-level systems using machine learning—particularly graph neural networks (GNNs) and
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full-time faculty members, whose principal research areas include Algebraic Semigroup Theory, Graph Theory, Mathematical Modeling in Medical Decision-Making, Mathematical Physics, Representation Theory
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on advancing the integration of gene regulatory network (GRN) simulations into multicellular and tissue-level systems using machine learning—particularly graph neural networks (GNNs) and reinforcement learning
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voting) and sampling problems (such as graph partitions for redistricting) and to launch new research in areas connected to the work of the lab. Members of the lab publish in peer-reviewed journals in
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date is 1 Januar 2026, with room for flexibility in both directions. We are seeking a highly motivated individual with a PhD in computer science, computational chemistry / biochemistry, applied
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Python, TensorFlow, PyTorch, or similar frameworks. MS or higher degree (PhD preferred) degree in Computational Neuroscience, Computer Science, Bioinformatics, or a related field with demonstrated ability
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detection, scene graph generation. A prospective method is transfer learning which freezes the backbone of the LiDAR-VLM model and fine tunes its output layers to adapt it to a particular task. An important