32 image-coding-"Foundation-for-Research-and-Technology-Hellas" PhD positions at Nature Careers in Germany
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, we are looking forward to your scientific support at the Clinic for Radiology! We are seeking a highly motivated PhD student to join our interdisciplinary research team working on multimodal imaging
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histological validation within murine cancer models. We offer an association with the Collaborative Research Centre 1450 “Insight – Multiscale imaging of organ-specific inflammation” graduate school
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location in Dortmund, we invite applications for a PhD Candidate (m/f/d): Mass Spectrometry Imaging The position is to be filled within the framework of the EU-funded project European doctorial network
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qualified women to apply for the position. Your tasks #designing, planning and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques #developing computational codes
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- Model-based assessment of climate impacts on conflicting land use systems Reference code: 50139755_2 Commencement date: August 1st, 2025 Work location: Hamburg Application deadline: 04.06.2025 The Climate
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- Participatory Methods for Impact chain assessment and backcasting Reference code: 50139757_2 Commencement date: August 1st, 2025 Work location: Hamburg Application deadline: 04.06.2025 The Climate Service Center
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PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
- Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress) Reference code: 50139753_2 Commencement date: 1st August 2025 or thereafter upon agreement Work location: Hamburg
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recommend checking out two exemplary recent publications (and maybe even the corresponding code and image repositories): You will be involved in writing scientific publications, presenting your research
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mechanisms underlying psychosis. The research utilizes advanced multiphoton imaging and virtual reality platform for simultaneous recording of animal behaviour and microcircuit activity. RESPONSIBILITIES
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning