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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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program, which includes tailored training, workshops, retreats, and conference travel. You will have access to cutting-edge laboratories and theoretical methods, individual supervision, and a wide range of
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: Prof. Dr. habil. Bilal Gökce), invites applications. RESPONSIBILITIES AND DUTIES As part of funded research activities, you will work independently on scientific questions related to the development
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qualified skills highly pursued by key technological players worldwide. The consortium of MATCH doctoral programme represents a multidisciplinary and intersectoral team with vast experience in training and
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and experience in the analysis of metagenomics and/or biological high-throughput
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) and the German Academic Exchange Service (DAAD) since 2007. Under this CAS-DAAD joint programme up and coming young Chinese scientists from the University of Chinese Academy of Sciences (UCAS) and CAS
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of Tübingen. The project is led by Principal Investigators Dr. Marlen Fröhlich, Prof. Dr. Michael Franke (both Tübingen) and Prof. Dr. Manuel Bohn (Lüneburg). The successful candidate will support the project
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the German Research Foundation (DFG), at the University of Tübingen. The project is led by Principal Investigators Prof. Dr. Michael Franke, Dr. Marlen Fröhlich (both Tübingen) and Prof. Dr. Manuel Bohn
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well as the changes affecting them. Join SEAMPHONI, an EU‑funded consortium of leading European marine research institutions, to pioneer methods for evaluating parasites of protists—especially phytoplankton—using eDNA