1,894 web-developer "https:" "https:" "https:" "Newcastle University" positions in Germany
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by regional train from Berlin-Lichtenberg). It also maintains research stations in Dedelow and Paulinenaue. With its Tenure Track System, ZALF aims to recruit excellent scientists with essential
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candidates which are explored in more depth. In particular you will work on the extension, development and analysis of new quantum algorithms for near-term and fault tolerant quantum computers for drug
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
deep learning (x/f/d/m) Background With the project Deepcloud, we will leverage the machine-learning revolution to understand clouds and their role in the climate system. We aim to train a deep learning
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
"Cloud physics" (f/d/m/x) Background With the project Deepcloud, we will use the machine-learning revolution to better understand clouds and their role in the climate system. We aim to train a deep
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development of climate-resilient tomato cultivars with improved growth and productivity under fluctuating environmental conditions. Tasks include analysis of the dynamics and responsiveness of gene expression
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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– ISAS – e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and therapy of diseases like cardiovascular diseases
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well as two insectaria (BSL-2/BSL-3). Eight research groups are currently based at the Institute of Immunology (IfI). Further information on the IfI can be found at https://www.fli.de/de/institute/institut-fuer
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, health-care, and MRI imaging. Our mission is not only to create accurate solutions but also quantify model uncertainties, analyze robustness, reliability, and trustworthiness of AI models, and develop
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the intersection of explainable artificial intelligence (XAI) and causal inference. Our goal is to develop AI systems that are causally understandable, such that predictions can be interpreted in terms of underlying