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Mathematics, Statistics, Epidemiology (human or veterinary), Public Health, Physics, Computer Science), and a history of productivity. Experience with stochastic simulation and model fitting to temporal and
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(STED) and Stochastic Optical Reconstruction Microscopy (STORM) Cryo-electron tomography Imaging data science and AI-based analysis A strong record of contributions to peer-reviewed research publications
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of development stochastic models that explain the population behaviour of immune cells subject to controlled stimulation, you will collaborate in research that seeks to explain the weak inheritance features
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University of Massachusetts Chan Medical School | Worcester, Massachusetts | United States | 2 months ago
, or ordinary/stochastic differential equations. • Experience in computational, statistical, or machine learning method development in any discipline. • Experience in analyzing high-dimensional data (biological
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, -- partial differential equations and in particular Navier-Stokes equations, -- stochastic analysis, -- mathematical theory for artificial intelligence, -- optimization and numerical computation over manifold
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of gene regulation, and transcriptional circuits including gene-regulatory networks, feedback regulation, and regulation of stochastic expression noise in multiple model systems ranging from viruses
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of gene regulation, and transcriptional circuits including gene-regulatory networks, feedback regulation, and regulation of stochastic expression noise in multiple model systems ranging from viruses
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the development of novel therapies for cancer, neurodegenerative conditions, and other diseases. We seek candidates with strong expertise in one or more of the following areas: stochastic processes and applied
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or computational modeling and a strong interest in interdisciplinary research. Experience in one or more of the following areas is desirable: Evolutionary theory, Dynamical systems, Stochastic modeling, Control
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. Methodological Areas of Interest Applicants with experience in the following areas are especially encouraged to apply: Optimization (deterministic, stochastic, robust, reinforcement learning–based) Systems