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have obtained a PhD degree in a relevant field and have a PhD-age of max 4 years per October 1st , 2024 (parental leave deducted). The postdoc candidate will be affiliated with the Philosophy Section
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directed to Associate Professor Helle Strandgaard Jensen (hs.jensen@cas.au.dk ) Qualifications A PhD in History, Cultural Studies, Anthropology, Sociology, Media Studies or related areas focusing on modern
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Two postdoc positions on the ecology and physiology of microbial key players exposed to oxygen de...
and energetic constrains ammonia-oxidizing and methane-oxidizing microbes exhibit under oxygen depletion (and while producing oxygen) including single cell activity assays. Applicants should have a PhD
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: PhD in computer science, machine learning, operations research, transportation engineering or a related field. Programming skills in C/C++ and Python, along with experience working with simulation
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will collaborate closely with a PhD student and the broader project team and will contribute to the implementation and follow-up of the randomized controlled trial evaluating internet-based therapy
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The successful candidates should have the following qualifications: A PhD in Environmental Toxicology, Chemical Engineering, Environmental Chemistry, Materials Science, or closely related fields. Solid
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evaluation process etc please visit: ambercofund.eu Qualification requirements Minimum requirements are: candidate needs to have a maximum of 8 years after a doctoral degree (PhD), as required by the project
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wishes to rely Copy of PhD diploma, if Phd diploma has not yet been received, please include statement from your supervisor Shortlisting may be used in the assessment process. Incomplete applications and
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have successfully defended a PhD thesis in a relevant discipline (computational mechanics, mechanical/aerospace engineering, simulation technology, applied mathematics, etc.). If you have not received
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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and