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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Outstanding Postdoctoral Training Strategy
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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vision, IoT sensors, and blockchain to monitor food quality, safety and animal welfare in real-time and enhance transparency. AI and machine learning will analyse data from pilot sites to identify
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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Researcher to join our team in reimagining how we discover and deploy drug combinations in the clinic. Our work is highly interdisciplinary, integrating high-throughput screening, state-of-the-art machine
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other