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Job Description We are seeking a motivated postdoc to work on the design and development of i) a variety of sample preparation methods (mainly for blood samples) and ii) new fiber-based substrates
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conferences, and actively participate in knowledge exchange across disciplines. As a formal qualification, you must hold a PhD degree (or equivalent). Specifically, a PhD in Materials Science and Engineering
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. Over the last decade HLA class II antigen presentation has been accurately described and methods developed that predict this event with a high level of confidence. In comparison, a detailed understanding
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have a few projects related to our novel method, AQUADA, which uses thermography and computer vision to detect damage in wind turbines and PV panels. We are looking for a new colleague to further develop
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forecasting. You will get the opportunity to participate and influence the development of advanced forecast solutions combining weather forecasts and novel machine learning/statistical forecasting methods
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. Qualifications: You should have (or be close to achieving) a PhD degree. Background within computational methods for inverse problems, ideally tomography. Experience with development of numerical implementations