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Field
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leverage their expertise to develop innovative algorithms for data analysis. Additionally, they will be responsible for communicating their findings to the scientific community through academic meetings and
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, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated
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of quantum field theory, mathematical aspects of string theory, general mathematical physics or quantum algorithms and quantum software development. We stress that candidates with an excellent research track
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The Position We are seeking an independent and motivated researcher for a Postdoctoral Fellowship in Aviv Regev’s lab to apply develop edge algorithms for analysis of single cell genomics profiles
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of