11 phd-position-data-mining Postdoctoral positions at Heidelberg University in Germany
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to evaluate strategies aimed at improving health outcomes among people treated in TB programmes worldwide. The position is suitable for candidates at PhD or postdoctoral level and is available for a duration of
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=26957 Mathematical Modeller (PhD/Postdoc) – Diagnostics for respiratory infections (m/f/d) PhD
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information for two individuals who can provide a reference. Please send this combined in a single PDF file to heike.kullmann@mwi.uni-heidelberg.de . For inquiries regarding the position, please contact Prof
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2026) with the possibility of an extension. The position is based at the Chair of Comparative Social Stratification (Waitkus) in the ERC funded project SOCDEBT – Towards a Sociology of Debt
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Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap-specific signals from raw
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platforms. The position is initially offered for two years, with the option of extension depending on performance and project continuation. We are looking for someone who enjoys growing with a young lab and
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offers a positions for a Post-doctoral scientist The position is available in the inspiring Heidelberg environment joining the Medical Faculty of Heidelberg University, EMBL and the DKFZ. The projects
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samples which are complemented by DNA methylation, DNA and RNA sequencing as well as clinical data. Together with the Artificial Intelligence and Cancer Evolution Division at the German Cancer Research
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of experiments in the framework of the scientific project plan Preparation and presentation of project reports and publications Your profile PhD in biology, biochemistry or equivalent Broad expertise in basic cell
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Heidelberg University and Stanford University, including population health researchers, clinicians, and methodologists. The researcher will lead analyses in large-scale electronic health record data