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biodiversity. Subject area Data-driven evolution and biodiversity concerns research that takes advantage of the massive data streams offered by techniques such as high-throughput sequencing of genomes and biomes
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. Two tracks to align with your goals: Choose between the academic or the entrepreneurial path. Global Collaboration: Opportunities for secondments at 29 renowned research institutions, infrastructures
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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interest in quantitative biology Curiosity and motivation in learning multiple -omics approaches Preferred experience includes familiarity with quantitative proteomics or NGS library generation Previous
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of proteomics and MS experiments in close collaboration with platform users and the team members, as well as sharing knowledge within the facility team. You will take part in multiple projects applied
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take pride in providing excellent technical support. As the workload will vary over time, you need strong time management skills and the ability to handle multiple projects of different sizes