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biological systems, also in collaboration with other researchers and companies. Your profile Applicants should hold a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Physics
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or a related field Solid experience within microbial fermentation either from your PhD or job in the industry Specific knowledge of process development and especially scale up Knowledge of large-scale
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qualification, you must hold a PhD degree or equivalent in chemical or mechanical engineering with the focus on fluid dynamics and energy systems. You will be assessed against the responsibilities 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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two PhD students in the groups, and your newly developed tools will support the analysis and interpretation of their data. You will interact strongly with several international collaborators, both
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visit our homepage . Expectations and qualifications Applicants must hold an MSc, DVM, or MD degree, and a PhD, with research experience within one or more of the following areas: Clinical or molecular
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: PhD in Veterinary Epidemiology or a related field, or demonstrated experience with epidemiology Strong quantitative data analysis skills Applied understanding of epidemiological principles Demonstrated
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. The department has a scientific staff of about 210 persons, 140 PhD Students, and a technical/administrative support staff of about 100 persons of which a large majority contributes to our research
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of the IML group within prediction of T cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics, postdocs and PhD students working on other projects within the group and
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the competences of the IML group within prediction of T cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics, postdocs and PhD students working on other projects within