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Apr 2026 - 23:00 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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for this position. Applicants should be proficient in R, Python, or equivalent statistical software. Some background knowledge in (computational) Bayesian methods and statistical learning for high-dimensional data is
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and quantitative imaging data Experience in computational modeling of gene regulation and morphogenesis Experience working on high-performance computing environments Personal skills Strong analytical
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, including RNA-seq, ChIP-seq, CUT&RUN, and related approaches Performing functional perturbation experiments and integrating multi-omics datasets Collaborating closely with experimental and computational
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and quantitative imaging data Experience in computational modeling of gene regulation and morphogenesis Experience working on high-performance computing environments Personal skills Strong analytical
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optimization for the compute continuum, across cyber-physical systems (CPS), distributed artificial intelligence (AI), and high-performance computing (HPC), from the data center to the edge devices
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, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The research group on statistical models for high-dimensional and functional
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, including RNA-seq, ChIP-seq, CUT&RUN, and related approaches Performing functional perturbation experiments and integrating multi-omics datasets Collaborating closely with experimental and computational
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sample collection through Biobank1, extracellular vesicles isolation from semen and urine, and downstream multi-omics data analysis. Duties of the position Conduct high-quality research following
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high-performance computing clusters is needed and knowledge of relevant programming languages (Python, Perl, R) is considered an advantage. A in-depth understanding of biochemistry, genomics experiments