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successful departments within the Faculty of Natural Sciences at Aarhus University. The department houses several of the Danish National Research Foundation’s Centres of Excellence and conducts teaching for
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the overall evaluation. Application procedure The faculty expects applicants to read How to apply before applying. The application must be in English and must include the following - the required forms can be
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, Logic, and Software Security , which has strong international presence and also ranks as a top-5 department worldwide in the area of Programming Languages ( https://csrankings.org ). See the Quantum
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successful departments within the Faculty of Natural Sciences at Aarhus University. The department houses several of the Danish National Research Foundation’s Centres of Excellence and conducts teaching for
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or women’s health. The applicant must be fluent in English (written and spoken) and have experience with large-scale health data and epidemiological or related analytical approaches and methodology. Experience
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documented research experience in a related field. The applicant should have experience in one or more of the areas/fields mentioned below Proficiency in programming languages such as Python or R. Experience
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Engineering & Structural Biology at https://www.biosustain.dtu.dk/research/research-areas/natural-products/enzyme-engineering-and-structural-biology If you are applying from abroad, you may find useful
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://www.space.dtu.dk/english/Research/Research-Divisions/Geodesy-and-Earth-Observation , And about DTU Space: https://www.space.dtu.dk/english If you are applying from abroad, you may find useful information on working
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field soil and will be conducted as part of the N2CROP project [https://mbg.au.dk/n2crop ]. Your profile We are looking for a highly motivated candidate with a keen interest in legume-rhizobium
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committed to diversity and encourages all qualified applicants to apply, regardless of their personal background. Given the nature of the project’s empirical work, applicants must be fluent, or near-fluent