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approach C4 Appropriate workload/time/project/budget/people management skills C5 Extensive IT and data analysis/interpretation skills as appropriate C6 Self motivation, initiative and independent thought
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 1 month ago
. The successful candidate will integrate multiscale first-principles modeling, sparse symbolic regression, and adaptive experimental design in self-driving laboratory settings to elucidate both desired catalytic
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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Ecology’s hub for accelerating connections between research, practice, and policy. PSIX is an emerging forward-thinking initiative dedicated to studying and advancing the science of purpose. By connecting
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(recruitment will be conducted until a suitable candidate is found). • candidates will be selected through an open competition, in accordance with the procedure consistent with the principles of the European
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the structural-property relationship in polymers through molecular engineering, structural engineering, and advanced characterization across scales. With these insights, we resolve conflicting design principles
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formation of polyhalogens. The applied methods will include first principles methods like DFT, both for finite and periodic systems, ab initio molecular dynamics simulations and calculations of various
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of the Principle Investigator, the primary purpose of the Postdoctoral Associate position is to perform specialized research activities and design and execute advanced experimental procedures in an immunology
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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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disclosure control as well as pseudonymization and anonymization techniques. Familiarity with the principles of differential privacy (DP). Knowledge of machine learning methods for generating synthetic data