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academic qualification (usually PhD). Tasks: independent, curiosity-driven basic scientific research on fundamental mathematical optimization problems in the fields of machine learning and image analysis
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the university The PhD programme does not offer any scholarship opportunities right now. However, the LMU offers divers funding possibilities. Please have a look at the LMU website: https://www.lmu.de/en/workspace
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chemical biology and biotechnology, enabling the preparation of defined oligonucleotides for a wide range of research applications. This project focuses on the experimental development and optimization
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 7 days ago
and optimization of solid-phase DNA synthesis methods, including reaction workflows, process parameters, and analytical evaluation of synthesized oligonucleotides. The work is part of an ongoing PhD
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available at https://www.fz-juelich.de/en/careers/phd In addition to exciting tasks and the collaborative working atmosphere at Forschungszentrum Jülich, we have a lot more to offer ( https://www.fz
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, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
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planning methodologies and in mathematical optimization techniques We are looking for first-class graduates with expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and
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fellowship programme (application deadline: 15 July). Submit application to https://www.ageing-grad-school.de/phd/applications Possibility of finding part-time employment Due to the intense nature
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local activation), multi-timescale adaptation (local memory), and stimulus-specific adaptation (multi-task processing). While the co-optimization of dendrite-inspired functional circuits with emerging
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the synthesis of drug-like compounds. Your tasks: As a PhD student in this Doctoral network you will use machine learning (ML) for the optimization of generality of synthetic methods. You will start with