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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems
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funded by a EU programme Reference Number 304--1-14162 Is the Job related to staff position within a Research Infrastructure? No Offer Description Join a research team developing state-of-the-art open
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in bioinformatics analysis and data visualization of our ongoing research projects on molecular characterization at the mRNA, miRNA, proteome and metabolome level from multiple lung compartments. Our
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and bioinformaticians to investigate the role of early life events in the development of early onset obstructive lung disease. Duties The overall project involves molecular characterization at the mRNA
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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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letter: - Protein expression in prokaryotes and/or yeasts - Experience with multiple protein purification techniques - Development of recombinant protein production protocols
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Exciting postdoc opportunity in integrating photosynthetic living organisms in materials and devices! Work assignments Are you passionate about developing the next generation sustainable