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Are you intrigued by the forefront of biophysics technology – and integration with genome-wide data and AI methods? Thanks to groundbreaking advancements, we can now show the internal dynamics
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ways in which such physical learning is realized, and design new types of learning machines capable of solving complex engineering problems on their own. Some examples include neuromorphic computers
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. These projects are at the interface of quantum physics, photonics, and nano-engineering. They have a mainly experimental character, but feature strong ties to the rich theoretical background. Our group offers
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. The need for such a technology comes from the the extreme miniaturisation of micro-electronics, which places extreme demands not just on nanofabrication, but also on inspection methods that visualize
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to contribute to new technologies that realize radical improvements in the energy efficiency of information and communication technology? As part of the Dutch consortium NL-ECO on energy-efficient computing
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fields, with many potential applications in engineering and medicine. In this project, you will study the spatial control of biochemical signaling in intestinal organoids and other 2D cell cultures
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follow individual cells as they grow, move, and differentiate to form branched duct architectures in mammary gland organoids. Using advanced 3D imaging, genetic engineering, and AI-driven cell tracking
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professionalization and further development of the role of the NanoLab as national facility. You coordinate the acquisition of new equipment and the development of processes and new technology, based on your knowledge
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improves through the experimentation process. Qualifications The internship is open to master’s degree candidates from a range of backgrounds, including Engineering, Physics, Computer Science, Mathematics
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candidates with a strong background in chemistry, physics, materials science, or engineering with an interest in self-assembly phenomena. Excellent candidates with training in any area of science or