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Description The Institute for X-ray Physics of the University of Göttingen welcomes applications for a PhD Position (f, m, d) starting as soon as possible. The salary is based on TV-L E13 (75 %, currently 29.85 hours/week). The position is funded by the German Federal Ministry of Research,...
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applications in information technology and are based on electrical, magnetic or optical functionalities. The Department of Quantum Technologies is looking for a PhD Student (f/m/d) - Imaging magnetic structures
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Join us to create new smart molecules for imaging of complex mechanics. Job description Soft matter such as polymers and hydrogels are incredibly versatile materials. Their use in metamaterials and
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PhD Studentship in Physiology and Pharmacology Project title: Visualising Platelet Biogenesis: Intravital Imaging of Megakaryocyte Signalling in Real Time (UK fees only) Supervisors: Dr Alex Bye
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electrode structures. • Prototyping of the identified structures via stereolithographic 3D printing and advanced textile techniques. • Development of advanced imaging and characterization technologies (X-ray
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Reference Number: 11180 Fixed-term of 3 years | Part-time with 65% (25 hours/week) | Salary according to TV-L EG13 | European Institute for Molecular Imaging We are UKM. We have a clear social
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A fully funded 3.5 years PhD position in the field of experimental nanoscience at surfaces and molecular imaging of conjugated polymers is available in the group of Prof. Giovanni Costantini at UoB
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“Spatiotemporal light shaping and photon counting cameras for microscopy” carried out within the FIRST TEAM FENG programme of the Foundation for Polish Science The aim of the project is to develop new imaging
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develop advanced nano-imaging and nano-sensing technologies, enhanced by AI analysis, to study viral infection in real time at the cellular and nanoscale level. This interdisciplinary research combines
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual