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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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background in molecular medicine or immunology. Experience with flow cytometry and animal models is a prerequisite, while basic understanding of extracellular vesicles will be an advantage. Research
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors, and more than 4 500 other faculty and staff working on our dynamic campus in
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project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting
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with all institutional training and code of conduct. Ability to work independently based on experience. Knowledge of molecular dynamics simulation and mathematical modeling. Qualifications REQUIRED
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, such as excited state methods, QM/MM simulations, molecular dynamics, simulating spectra, analyzing charges and molecular or environmental configurations, along with experience coding in python. Application
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of optical technologies. You may also: Have expertise in theoretical modelling and simulation of optical devices. Possess experience in experimental semiconductor device physics and electronics. Demonstrate
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, implementing the QTAG approach in a computer code, and testing and benchmarking it on model systems relevant to chemistry. Job Related Minimum Required Education and Experience Requires a Doctoral (Ph.D.) degree
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proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation of material properties, electronic structure, and atomic-scale behavior
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 24 hours ago
), expertise in computational modeling (such as Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication