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Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Expertise in or a strong interest in machine learning and deep learning algorithms. · Excellent communication skills
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experience in deep learning frameworks (TensorFlow/PyTorch) Experience with large-scale genomic/proteomic datasets and machine learning applied to biological sequences Knowledge of phylogenetics, protein
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular
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A PhD in immunology or related field with a deep understanding of mucosal immunology is required. Expertise working with primary human cells, intestinal tissues/organoids, murine models of intestinal
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own surveys and secondary data collected by third parties. The ideal candidate for the position will be a recent PhD graduate with a deep interest in this domain who can provide research support in
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graduation. An excellent academic record, a deep understanding of immunology/immunotherapy (human/mouse) as well as practical experience of immune cell biology, cell culture, gene edition (crispr/cas), flow
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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with health surveillance and related data to estimate climate-attributable risk under Deep Uncertainty. The candidate will also contribute to the development of interactive tools and training materials
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exceptional postdoctoral research fellows interested in developing deep learning and computational methods for pathology image analysis, multimodal data integration, and other medical modalities (e.g