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Term: 1-2 years renewable Appointment Start Date: asap Group or Departmental Website: https://med.stanford.edu/content/sm/kramsmartinezlabs.html/(link is external) How to Submit Application Materials
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preferred, but not required) are desired. Experiences with catalysis (biological, homogeneous, or heterogeneous), excited-state simulation methods, multiscale simulations (broadly defined), molecular dynamics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Preferred Qualifications, Competencies, and Experience Programming skills (e.g., python, bash scripting, Fortran, C++ and CUDA), expertise in computational modeling (such as Deep Learning, Molecular Dynamics
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A postdoctoral fellow position is available at the Icahn School of Medicine at Mount Sinai, New York, at the laboratory of Dr. Eirini Papapetrou https://labs.icahn.mssm.edu/papapetroulab/ and the
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on the development of hybrid QM/MM methodologies, machine learning approaches, and advanced free energy simulation methods. These methods are applied to investigate enzyme catalysis, conformational dynamics
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to diseases such as cystic fibrosis and chronic obstructive pulmonary disease, with particular emphasis on epithelial and immune cell interactions, inflammatory memory, and host pathogen dynamics. Research
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ABIF can be found at: http://www.mcgill.ca/abif. Primary Responsibilities 1. Technical Development & Innovation Lead and document quality control (QC) workflows for ABIF imaging systems, including
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molecular dynamics simulations, applicable to materials science, biomolecules, or a related field. Programming experience (e.g., Python), with a strong background in developing and applying computational
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of persistent quantum entanglement. Essential Duties and Responsibilities: The successful candidate will operate in a friendly and dynamic team environment of the Condensed Matter Theory Group, with opportunities
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will work on a DOE-funded SciDAC project Moving Electrons through Space and Time: Enabling the Quantum Dynamics of Chirality-Induced Spin Selection Through Novel and Scalable Computational Methods