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, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we educate innovative
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Kibsgaard and Professor Stig Helveg, DTU Physics. We favour candidates with a degree in physics, chemistry or materials science. The candidate should preferably have experience in electron microscopy
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Sciences Internal Number: 6472603 Research Assistant Professor of Neuroscience Location: Philadelphia, PA Open Date: Dec 17, 2024 Deadline: Dec 17, 2026 at 11:59 PM Eastern Time The Department
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 3 days ago
21 Aug 2025 Job Information Organisation/Company Leibniz-Institute for Plant Genetics and Crop Plant Research Research Field Agricultural sciences » Agronomics Agricultural sciences » Other
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partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a
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change theory and practice, implementation science, and associated measurement and analytic techniques. The candidate is expected to help bridge these domains using validated statistical tools. Applicants
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. Responsibilities and qualifications Your overall focus will be to establish and lead a strong research program in the field of synthetic biology and metabolic engineering of non-model microorganisms, with the aim
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Degree PhD Course location Potsdam In cooperation with The innovative PhD and postdoctoral programme is offered in conjunction with the Faculty of Digital Engineering, a faculty jointly founded by
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Job Description Are you passionate about metabolic engineering of bacteria? Do you want to contribute to solving urgent problems with synthetic biology? The Systems Environmental Microbiology (SEM
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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition