11 parallel-and-distributed-computing-phd positions at Centre for Genomic Regulation in Spain
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Barcelona, Spain, invites outstanding and motivated candidates from across the world to apply for itsInternational PhD Programme 2027. Why join the Centre for Genomic Regulation? Work alongside world-class
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massively parallel selection experiments to tackle the fundamental encoding problems of molecular biology. Towards this goal we have developed, benchmarked, and applied at scale experimental methods that use
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applications with related expertise. Experience with sequencing approaches to study RNA turnover or with massively parallel reporter assays(MPRAs) will be beneficial. Must Have Bioinformatics experience in
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Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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shotgun sequencing data, detecting horizontal transmission). We are mostly computational, but have a small lab component and work in close collaboration with the CRG core units for metagenome sequencing. We
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of RNA-binding proteins involved in melanoma progression. Appropriate candidates should have expertise on 2D-PAGE and analysis of protein phosphorylation. Candidates must hold a PhD degree and be fairly
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effects) and metagenomics (microbiome profiling using deep shotgun sequencing data, detecting horizontal transmission). We are mostly computational but have a small lab component and work in close
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effects) and metagenomics (microbiome profiling using deep shotgun sequencing data, detecting horizontal transmission). We are mostly computational but have a small lab component and work in close
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the field of molecular and cellular biology You have advance knowledge of bioinformatic analysis Education and training You hold a PhD in Biology or equivalent Languages You are proficient in English
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-based principles. The successful candidate will train, benchmark, and develop deep learning architectures. They will work in high-performance computing environments and apply expertise in statistical