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and function in a collection of maize germplasm exhibiting diverse levels of yield stability under drought stress. The high-level objective of the research is to characterize the processes of water
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
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microbiota composition and function in a collection of maize germplasm exhibiting diverse levels of yield stability under drought stress. The high-level objective of the research is to characterize
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processing Strong experience in machine learning or deep learning for medical image analysis Strong programming skills in Python, with additional experience in C/C++ or other object oriented languages
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in machine learning or deep learning for medical image analysis Strong programming skills in Python, with additional experience in C/C++ or other object oriented languages Experience with PyTorch
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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the research area; gathering, analysing and illuminating data, evaluate and criticise texts and bring new insights to research area; supporting the development of research objectives and proposals for own and/or
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candidate will carry out duties to the highest standard and will: Undertake original research of international excellence. Develop research objectives and proposals for own and/or collaborative research
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Postdoctoral Researcher position in the group of Prof. Gunda Köllensperger. The major objective is to downscale metabolomic techniques to the level of organelles, small cellular communities ultimately aiming
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analysis Strong programming skills in Python, with additional experience in C/C++ or other object oriented languages Experience with PyTorch/TensorFlow for computer vision tasks Track record of publications