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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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thermal signals with high sensitivity and nanoscale spatial resolution, opening access to biophysical structure and dynamics that are difficult or impossible to reach with conventional techniques
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engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based surrogate model discovery are strongly
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, cohesive zone modeling, and will interface with the molecular dynamics group to create customized scripts for implementing. Responsibilties: Conducting experimental research Conducting theoretical research
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at least one of the following areas: excited-state simulation methods, multiscale simulations (QM/MM a plus), catalysis (biological, homogeneous, or heterogeneous), molecular dynamics simulations, sampling
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a Postdoctoral Research Associate to train in interdisciplinary projects involving developing new AI-driven Molecular Dynamics (MD) simulation methods and apply them to drug discovery in multiple
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behavior and nonlinear dynamics. The position also includes mentoring graduate and undergraduate researchers and contributing to sponsored research reporting. This is a full-time, fixed-term postdoctoral
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to detail · Proactive, and able to work collaboratively as part of a dynamic, diverse, and growing team Application Materials If interested in the position, please provide a CV, contact of three references
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microfluidics channels experimentally. The particle dynamics under solute concentration gradient will be analyzed and new methods of manipulating particles in complex geometries will be developed. Application
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based