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scientific publication, grant-writing and outreach, relevant research techniques and skills, and have opportunities to build connections with broader networks of scholars studying restoration social science in
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that are implemented for an entire shipping corridor, or various bunker infrastructure strategies in the network. In addition, the impact of the feasible interventions can be evaluated, ranging from the individual ship
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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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with leading European research organisations and stakeholder networks while contributing to high-quality scientific outputs, project deliverables, and dissemination activities. The ideal candidate will
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cancer. The Di Stefano Lab employs cutting-edge genomic and molecular approaches that includes ribosome profiling, eCLIP-seq, and single-cell multiomics—to define gene regulatory networks at systems-wide
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 18 hours ago
new areas of basic and applied research Transition classroom theory into hands-on experience Network with world-class scientists Exchange ideas and skills with the Laboratory community Use state
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scientists, software engineers, data managers, and collaborators across the Mahidol Oxford Tropical Medicine Research Unit, and the wider Tropical Network Programme. Wet lab work will not be involved in
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corridor, or various bunker infrastructure strategies in the network. In addition, the impact of the feasible interventions can be evaluated, ranging from the individual ship level and its emissions
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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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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations