86 programming-"the"-"DAAD"-"EURAXESS"-"IMPRS-ML"-"O.P"-"U"-"UCL" "https:" PhD positions in Denmark
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duration of 3 years. Applications for a 4+4 PhD programme are also welcome. The proposed starting time is spring 2026, with some room for flexibility. The appointment will be made at a competitive salary and
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the research group Bioactives Analysis and Applications, and as part of the prestigious Alliance PhD program, you will collaborate with the Technical University of Munich (Germany). If you're ready to
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. Further information for international applicants about entering and working in Denmark. For further information about the PhD program at the department, read here: https://sdunet.dk/en/enheder/institutter
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made through
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, skills and achievements that demonstrate the ability or potential to produce high quality research outputs and publish in journals A personal research plan which is consistent with the project Experience
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achievements that demonstrate the ability or potential to produce high quality research outputs and publish in journals. A personal research plan which is consistent with the project. Experience, skills and
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) Programming experience (e.g., Python, Julia) Strong analytical thinking and problem-solving abilities Interest in power and energy systems Excellent English communication skills and a collaborative mindset to
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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are looking for candidates who have experience with developing AI or machine learning models, as well as bacterial sequence analysis. You should be familiar with relevant programming languages such as Python