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the Computer Science study program. The stipend is open for appointment from August 1st 2025 or soon thereafter. The PhD students will be working on topics within the general areas of formal methods, model checking and
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have not completed an English language-based Master's programme (or an equivalent educational achievement in English) shall provide documentation that they have passed one of the following official tests
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with the following engineering tools and programming languages can be an advantage but not limited to: MATLAB, PLECS, PSCAD, others Excellent English language skills (both oral and written). Publications
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an English language-based Master's programme(or an equivalent educational achievement in English) shall provide documentation that they have passed one of the following official tests with the respective minimum score
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, control theory. Excellent spoken and written communication skills in English are expected. Application An application must contain: 1. A cover letter of max. 2 pages (excl. references), including (i
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on the PhD programme, application procedure, and admission requirements. The application must include the following and be written in English or Danish: Copy of diplomas/transcripts List of written work
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. At the Faculty of Engineering and Science, Department of Chemistry and Bioscience, a PhD stipend within the EU HORIZON/Marie Sklodowska-Curie Actions is available within the general study program. The PhD stipend
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to complete a doctoral thesis in English and who do not have English as a first language or WHO have not completed an English language-based Master's programme(or an equivalent educational achievement in
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. Documented experience with any project in the blue bioeconomy domain, with Life Cycle Assessment, and with programming for data science(R, python) will be considered a strong plus. Proficiency in English is a
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Research, Computer Science, Mathematics, Applied Mathematics, or related fields. Proficiency in programming languages such as Python, R, or other programming languages. Familiarity with multi-agent systems