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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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-Firmenticket that is partially subsidized. This is a fixed-term position limited to a period of 3 years. Remuneration is paid according to TVöD Bund, salary group 14. Application and information: We value
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the project »MoGeSa« and develop a detailed Modelica-based simulation model of a floating wind platform for a 15 MW offshore wind turbine. As part of this, you will perform a large number of simulations using
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Performing atom probe tomography Application of deep learning algorithms for the correlation of the obtained experimental data and their analysis The majority of the work will be undertaken in Hamburg Your
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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maintain pipelines for the analysis of high-throughput sequencing data, including RNA-seq, ChIP-seq, ATAC-seq, and single-cell and spatial omics. Integrate machine learning and large language models (LLMs
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requirements are Experience in working with large-scale spatial-temporal traffic and/or travel behavior data, e.g., loop detector, floating car data, GPS data, cellphone data. Experience with transport
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serve as a central hub for industry, academia, and policy-making. Together with international research partners, we develop information-theoretically grounded and application-driven algorithms in