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Field
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missions. Prior experience with methods of statistical inference using simulations or anomaly searches with machine-learning approaches is desirable.
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challenges, the school provides a wide variety of topics, from logic in autonomous cyber-physical systems to machine learning in Earth System models. You will have one supervisor from the mathematical sciences
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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-cell genomics data, ideally using tools such as Seurat or Scanpy Enthusiasm for statistical modeling and machine learning to analyze complex biological datasets High level of care and attention to detail
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
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Jyvaskyla University of Manchester Kone Oyi The candidates will have the opportunity to visit various partners in the network, supported by a mobility allowance. At the Chair of Machine Learning for Complex
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research group (please find further information at https://www.biologie.uni-konstanz.de/gruber ). You will be developing machine learning-based data science approaches for the analysis of Next Generation
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
polyoxometalates Using suitable characterization methods to characterize the synthesized materials Using machine learning tools to tune the synthesis parameters in a feedback loop and enhance the properties
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one