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, we work together to find solutions that best promote their abilities. With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 22 days ago
. This PhD project focuses on developing next-generation optical microscopy methods that push both spatial and temporal resolution, enabling nanoscale, real-time observation of cellular dynamics currently
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that Feed the World” with the aims: 1. To train and develop future leaders in science, industry and society who excel in research, management and communication. This will be achieved by implementing a
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part of change Contributing to the development of the next generation optical wireless communication systems Familiarization with physcial layer and technical basics of optical wireless communication and
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Chair of Biological Imaging 27.02.2026, Academic staff We are now seeking a highly qualified and motivated Ph.D. student (f/m/x) to drive the development of novel optical technologies addressing
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computational simulations to understand the combustion of solid propellants across different scales. You will further develop an existing simulation code based on the discontinuous Galerkin method. In doing so
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computational simulations to understand the combustion of solid propellants across different scales. You will further develop an existing simulation code based on the discontinuous Galerkin method. In doing so
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validate and further develop our models. The focus of this project lies on combustion kinetics. The objective is to develop a mesoscale description of solid propellant combustion based on global chemical
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ranges from biostatistical consulting and statistical analysis of biomedical data to the development of complex methods for specific scientific questions. The application of new techniques in the rapidly
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of machine learning for engineering applications to start as soon as possible. Be part of change Developing and benchmarking Neural Network architectures (Graph Neural Networks, Transformers, etc