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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research
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PhD Position (m/f/d) - Atomic Layer Deposition (ALD) of transition metals for biomedical application
The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sus-tainable
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to integrate variety and crop mixtures into breeding practices to bolster resilience and adaptability against climate change. By exploring the genetic architecture of crop mixtures and developing predictive
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The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sustainable materials
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with a focus on transnational terrorism or related topics in international academic journals and with well-established publishers; Development of grant applications and implementation of research
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separation") within the framework of Horizon Europe. PhotoBrane is at the forefront of innovation, developing next-generation phototunable and photoregenerable membranes. These breakthrough membranes can
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research and scientific methods relevant for research in behavior and ecology. The unique opportunity to gain field experience in a West African national park, train with experienced behavioral biologists
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. Our research combines computational chemistry, cheminformatics, bioinformatic and AI to design new molecules and enzymes for unprecedented catalytic functions. In this project, you will: Develop
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Association with an international reputation and globally networked research infrastructure. It is active in three closely interlinked fields: collection-based research, collection development and cataloguing
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You