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, or network-based, Bayesian or matrix factorization methods for multi-omics integration Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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of large-scale multi-omics cancer data. Proven experience in development of bioinformatics tools and software packages. In-depth knowledge in NGS data processing from whole genome sequencing and RNA-seq
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quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering, hardware-software integration, image analysis. Building quantitative models: Using high-throughput binding data
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in Sweden at large. For information about the SciLifeLab fellow program, see https://www.scilifelab.se/research/#fellows . SciLifeLab Fellows are also part of a broad national network of future
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program (Data-Driven Life Science) with focus on precision medicine. Access to top-level infrastructure, a new therapy development initiative for brain diseases (CNSx3), and a strong network spanning
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data. For this, the applicant will generate in silico datasets from diverse computational models of development, such as models of tooth development and gene regulatory networks. They will leverage
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal