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Field
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spoken English. Strong analytical skills. Willingness to acquire a variety of additional skills ranging from physics modelling and statistical data analysis to hardware programming. PhD researchers
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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the use of instrumental analytical methods such as HPLC-MS, GC-MS knowledge in the preparation of plant tissues for the extraction of natural substances experience in the application of molecular biological
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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especially to the ‘EA FC’ game, formerly known as the ‘FIFA game’. Its popularity positions the game as an informal learning site for ideas about societal issues. This includes ideas about race and ethnicity
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and the data analyses of mass spectrometry data. Attending a total of six months secondments to learn novel algorithms form improving fecal MP samples' taxonomic and functional characterization
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of the research group. Desired qualifications and skills: A relevant background in aquatic biology, animal physiology or a related field. Good skills for laboratory-based analytical tools. Practical experience
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and Artificial