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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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record relative to career stage Excellent written and spoken English communication skills Following qualifications will be considered as an advantage: Experience with explainable AI methods Experience with
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such as data scarcity, cultural sensitivity, inclusivity, and the need for robust preference optimization methods that go beyond standard fine-tuning. Key research objectives include: Developing Efficient
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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
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resource recovery pipelines You will contribute to the translation of structural and biophysical insights into technologies or methods for transforming recovered biopolymers into valuable products or process
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biological problems and is thus not focused on development of computational methods. We wish to generate small protein binders against a range of important neuroscience targets – principally intrinsically
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of field-grown vegetables or agricultural crops, and master state-of-the-art experimental and analytical methods in plant physiology, agronomy and agroecological research. You are expected to have research