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Researcher (R1) Positions PhD Positions Application Deadline 31 Mar 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 May 2026
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algorithms to understand how perturbations to dynamic brain networks impact seizure likelihood. With an emphasis on the emerging field of digital twins for personalised health, the ultimate aim is to translate
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at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd Place of employment: Wuppertal We welcome applications from people with diverse backgrounds
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Funding for: UK Students Funding amount: Funding will cover tuition fees for UK students (at the Home rate), a stipend at the UKRI rate , and a consumables budget. This is a 3.5-year PhD
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(SBiK-F) Research Field Biological sciences » Biodiversity Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 6 Apr 2026 - 00:00 (Europe/Berlin) Country Germany
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), the MADBARLEY project will identify and characterize central regulators of the thermotolerance signalling network in barley. The successful candidate will employ (phospho-)proteomics and metabolomics to identify
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Neuromorphic Architecture for Low-Power Spiking Neural Networks. PhD thesis, Université Côte d’Azur, 2022. A. Abderrahmane et al. Event-based neuromorphic computing: A survey. Proceedings of the IEEE, 108(8
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research project. You will be given opportunities to participate at national and international meetings and establish your network. We offer a competitive salary (https://www.kuleuven.be/personeel/jobsite/en
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is an inclusive community of and for all PhD students at Ghent University. A network of enthusiastic and dynamic PhD students is operating as PhD ambassadors that transcends the boundaries of faculties
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Degree PhD – Dr rer nat Doctoral degree or degree awarded by Ludwig Maximilians University of Munich or Technical University of Munich Course location München In cooperation with LMU Munich, Max