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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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after a positive evaluation is possible and aspired. Your responsibilities We are looking for a motivated researcher who is passionate about data and shares the RDC’s vision of making complex microdata
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the programme area ‘Plant Adaptation’ (ADAPT). The aim of the research project is to understand how intrinsically disordered regions (IDRs) and prion-like domains (PLDs) control the temperature responsiveness
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QCLs) for high-resolution spectroscopy. Within the framework of the priority program INtegrated TERahErtz sySTems Enabling Novel Functionality (INTEREST) funded by the German Research Foundation (DFG
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an interdisciplinary environment, very good communication skills in English; willingness to acquire German language skills is expected and will be encouraged Desirable skills PhD in biodiversity informatics
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funded by the Leibniz Collaborative Excellence program and conducted in cooperation with the Institute of Space Systems at the University of Stuttgart. The position includes setting up a multi-metal lidar
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is beneficial We encourage you to apply even if you do not meet every requirement. We value diverse perspectives and are committed to finding the best candidate, recognizing that growth and learning