User Profile

cnls


Status:
Other
Location:
Los Alamos National Lab, New Mexico, USA
Research Interests:
Statistical Mechanics Beyond Equilibrium (Strength of materials, Fluid Turbulence and Mixing, Macroscopic quantum systems, Mathematical physics of multiscale problems) Statistical Physics of Networks, Information and Complex Systems (Neural computation, Network theory, Information theory) Complex Biological and Bio‐inspired Systems (Simulations of biochemical reaction kinetics, Nano‐Tubes, Self‐assembled thin films, Bio‐Polymers, Quantum Chemistry)
Affiliations:
Los Alamos National Laboratory
About cnls:
The Center for Nonlinear Studies (CNLS) is part of Los Alamos National Laboratory's Theoretical Division. We organize research related to nonlinear and complex systems phenomena. CNLS was formed in October of 1980.

CNLS Mission Statement

* Identify and study complex nonlinear phenomena using a diverse set of research approaches and methodologies, particularly those of statistical physics, nonlinear science, applied mathematics and numerical simulation.
* Promote the use of scientific results in applied research.
* Stimulate the formation of interdisciplinary approaches to complex problems.
* Facilitate the interchange of scientific results and ideas between Laboratory scientists and external centers of excellence.
* Encourage the exploration of new scientific frontiers at the interface between conventional disciplines.
* Support a broad spectrum of interdisciplinary science that underpins the Laboratory’s mission in national security.
History of Education and Employment
Postdoctoral Positions Available

The Center for Nonlinear Studies (CNLS) at the Los Alamos National Laboratory is seeking candidates for Postdoctoral Research. Areas of interest include:

* multiscale phenomena in materials, discrete simulation of nonlinear systems,
* probabilistic and combinatorial analysis of biological systems,
* applications of nonlinear and stochastic dynamics,
* self-organization and pattern formation,
* landscapes and dynamics of proteins.

Applications of these studies to condensed matter physics, fluid dynamics, plasma physics, chemistry, materials science, theoretical biology, and computational science (e.g., neural networks, parallel computation) are being actively pursued.