500 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Goethe-University" positions in Denmark
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to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a shortlisting
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data We are looking for a candidate with a structured working style and the ability to multitask with attention to detail. You must have a positive mindset and willingness to take on both routine and
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workplace here You can read more on Department of Sustainability and Planning here You may obtain further professional information from Associate Professor Troels Krarup, e-mail troelsmk@plan.aau.dk or phone
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, high-throughput screening, and state-of-the-art carbohydrate analysis, to validate computational designs and generate data that advances our knowledge of enzymatic carbohydrate synthesis towards
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The project may address national or international problems, and should do so using appropriate methods, qualitative and/or quantitative. Access to Danish data sources, such as registry data, respondents
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omics data. In your daily work, you have a close interaction with competent colleagues. Your main tasks will consist of: Maintain and differentiate human stem cells (essential) Generate and maintain brain
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reactors Maintain detailed records of experimental data, process conditions, and system modifications. Publish scientific articles based on data collected during the research, development, and innovation
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; mepage.faculty.ucdavis.edu ). Simonsen will be the main advisor to the PhD student. Her research studies policies that directly or indirectly affect children’s outcomes and she is an expert on the Danish administrative data
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requirements using pilot-scale or simulation data Publish high-impact research results and present findings at international conferences Contribute to proposal writing and joint projects with academic and
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charging strategies for lithium-ion batteries. The goal is to integrate model-based (digital twin) and data-driven (AI) methods to design and experimentally validate optimized pulse charging protocols. A