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Field
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criteria Experience with laboratory development in power electronics would be desired. Scientific publications will be merited. Experience with programming tools (e.g., Python, Matlab, C/C++) will be merited
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of the largest, most international and most innovative employers in the region. With more than 6 000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top
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enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your ideas with AND without LLMs. You get excited about implementing your
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must have a solid background in mathematics or physics, and good programming skills (e.g. Python or MATLAB). You must meet the requirements for admission to the Faculty's PhD programme in Electronics and
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at the intersection of genetics, epidemiology, and cardiovascular medicine. Using large-scale genetic and health registry data, you will investigate sex-specific differences in stroke risk among patients with atrial
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photochemically formed secondary air pollutants such as ozone and particulate matter. Secondly, a very large number of different hydrocarbons are emitted which makes their inclusion on air quality model difficult
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traffic flow theory and simulation. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your
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Assessment Model combining verifiable, self-reported and observable interaction data. Investigate how interviewers weight different sources of evidence and how cognitive, social and cultural biases affect
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, and increasing data complexity, as well as how monitoring approaches can be designed to remain effective across different marine contexts and scales. The successful candidate will contribute
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up to 2050. Quantifying the environmental impacts of primary and secondary steel production under different future scenarios, including climate change, energy and resource use, water consumption, waste