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Field
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via nonlinear parametrizations such as deep networks, dynamical systems and control, Bayesian inference and generative modeling, and randomized linear algebra. Applications of interest are transport
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. The position involves data analysis, model development, use of AI/ML tools for both understanding the mechanisms governing long-term performance of polymers and composites and translating findings into practical
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oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover
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statistical modeling and analysis of human performance data (reaction time, workload, situation awareness), including mixed-effects/multilevel models. Programming proficiency in Python, R, and/or MATLAB
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. Training is available in a variety of super-resolution quantitative microscopy and image analysis techniques, and mass spectrometry. PI commitment to mentoring and career development opportunities tailored
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Perform NGS library preparations, such as whole-genome and whole-exome sequencing, 10x RNA-seq, etc. Perform cell culture procedures, including culture of primary cells, flow cytometry, single cell analysis
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: A WashU-funded study examining patient navigation and human-centered design approaches in cancer care in Kenya. The fellow will support study coordination, data analysis, and dissemination. • PRIME-KS
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/ ). Together, CAHBIR, the CCNP, and a broad network of Rutgers-affiliated clinical partners provide an exceptional environment for training in clinically focused computational and cognitive neuroscience research
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the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes
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such as transformers, self-supervised learning, multimodal learning, generative models, graph neural networks, or foundation models. Experience with structural and/or functional brain modeling. Familiarity