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analysis. Specifically, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws
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Analysis: Experience with programming (for example Python/Matlab) and image analysis is highly emphasized. Such experience should be documented. Scientific Curiosity: You are eager to bridge the gap between
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techniques, as well as cell culturing techniques Molecular biology techniques and digital image analysis Analysis of high-throughput datasets (RNA seq, proteomic data) Publications in international peer
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provided with office space, equipment, and services as well as necessary resources for research related field work and conference travel. Your areas of responsibility Participate in data analysis Contribute
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. Experience with programming (for example Python/Matlab) and image analysis is highly recommended. Please share your GitHub code repository if you have one. In assessing the applications, special emphasis will
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advantageous: Immunohistochemical/immunofluorescence techniques, as well as cell culturing techniques Molecular biology techniques and digital image analysis Analysis of high-throughput datasets (RNA seq
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electricity/electronics, chemistry, and optics, as you will be working with advanced custom instrumentation. Experience with programming (for example Python/Matlab) and image analysis is highly recommended
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by writing analysis scripts in e.g. Matlab. The candidate is expected to present their research at national and international conferences Qualification requirements Applicants must hold a Master’s
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written. Motivation to work with analysis and publications from various studies. Personal qualities Good communication- and collaboration skills in an interdisciplinary research environment. Ability to work