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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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Job Description Job Responsibilities -Conduct molecular dynamic (MD) simulations of the interactions of biological toxins including alpha-toxin, pyocyanin, and pyoverdine with clay natural and modified
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Number: 256245 Minimum Education and Experience: The ideal candidate should have a PhD in plant molecular biology or genetics. Candidate should also have a record of submitting manuscripts through the peer
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system related to different replication stages of the HIV virus. Preference will be given to applications with expertise in 1) protein dynamics; 2) molecular dynamics simulations; and 3) high-performance
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Dynamic GRNs from scRNA-seq + scATAC-seq Cell state-specific causal GRNs from population-scale scRNA-seq We continue to push the boundaries of reverse-engineering molecular interactions from observational
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the position. Experience in basic cell and molecular biology techniques in kidney disease research. Preferred Qualifications: The candidate should have: * Background in cell/molecular biology. * Experience with
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related field. Ability to demonstrate professional competence in relevant research activities related to molecular bioengineering and biotechnology. Specialized training and experience in operating
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simulations to identify key mechanistic drivers of viral persistence and immune response, and use SciML to automatically select ODE/PDE models that include these mechanisms. The postdoc will develop
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the start of the position. Experience in basic cell and molecular biology techniques in kidney disease research. Preferred Qualifications: The candidate should have: ● Background in cell/molecular biology
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the start of the position. Experience in basic cell and molecular biology techniques in kidney disease research. Preferred Qualifications: The candidate should have: ● Background in cell/molecular biology