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underrepresented in science, who have curiosity, creativity and a drive to learn new skills. Not all projects will be funded; a limited number of candidates will be appointed via a competitive process. English language
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Engineering to educate the next generation of global leaders. Multidisciplinary research and exceptional teaching in a highly diverse and inclusive campus community are hallmarks of the University’s mission
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the Paris region specializing in environmental and climate sciences at the Institut Pierre-Simon Laplace (IPSL) (https://www.ipsl.fr ). The LOCEAN team's work focuses on studying the physical processes
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such as articles and your PhD thesis (provide an English summary if the thesis is not in English) that you have authored or co-authored. The following experience will strengthen your application: A doctoral
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professionally and personally. For more information about the working conditions, please visit: https://www.universiteitleiden.nl/en/working-at/job-application-procedure-and-employment-conditions What we find
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with evidence of successful goal-setting and team performance. Academic Excellence: A PhD (or equivalent expertise) in English and/or Creative Writing (or related subject). Professional Profile: A strong
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quality research and participate in transdisciplinary research Proficiency with computer programming languages (Python, R or related language) The selected appointee must enroll as a PhD student at the
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AI tools for creative design processes LanguagesENGLISHLevelExcellent LanguagesGREEKLevelMother Tongue Research FieldEngineering » Design engineering Internal Application form(s) needed Proposal
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, Social Sciences, Natural Sciences, Health Sciences, or Engineering by the call deadline (date of PhD defence/viva) Have a maximum of 8 years full-time equivalent research experience measured from the date
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular