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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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research in our lab can be found at: http://www.thechenglab.org/publications.html . A candidate is expected to collaborate closely with experimental biologists and clinicians. The position offers
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processing algorithms, build a Dash-based GUI, and develop standardized analysis pipelines. The role includes community-oriented tasks such as documentation, tutorials, and user support. The work requires
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for mobile communications and radar systems. We are looking for motivated postdoctoral research candidates to participate in the development of signal processing algorithms for multi-antenna integrated sensing
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mechanics/molecular mechanics (QM/MM) calculations are used to examine chemical reactions occurred in enzymes. Furthermore, we develop novel simulation algorithms and new models for biomolecules to overcome
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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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terms of universal computational skills. We encourage you to describe your work using broader technical terms—such as "statistical data analysis," "workflow automation," or "algorithm optimization"—rather
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in Ithaca, NY with a focus on developing deep learning algorithms. Dr. Haiyuan Yu, Ph.D. is a Tisch University Professor of Computational Biology in the College of Agriculture and Life Sciences and a
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning
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variety of cutting-edge research in time-domain astrophysics, including the development and implementation of machine learning, statistical and data-driven algorithms to study exotic transient phenomena