37 postdoc-in-postdoc-in-automation-and-control-"Multiple" positions at SciLifeLab in Sweden
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, as well as on local servers. Automating data handling and integrating systems for laboratory tracking (samples, steps, reagents), document management, and KPI visualization. Developing and supporting
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Department of Pharmacy, and SciLifeLab DDD. The role entails close collaboration with researchers across multiple institutions in Sweden and internationally. The position includes close work within ongoing and
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sites at Umeå university with over 20 bioinformaticians supporting multiple research fields, hosted at the Department of Plant Physiology. The workplace is located right at the Chemical-Biological Centre
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postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and
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initiatives in applications of genomics and proteomics Integrate sequencing data from external and public resources to improve clinical research outcome Supervise postdocs, graduate students and technical
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Experience with long-read sequencing technologies and related data analysis Experience with automation of lab procedures and liquid handling systems Previous project management experience Good oral and written
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multiple locations in Sweden. It serves as the bioinformatics platform at SciLifeLab, a national resource that facilitates research in molecular biosciences by offering access to state-of-the-art
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databases such as KEGG, Reactome, and GO. Pipeline Development: Development and maintenance of reproducible pipelines (Snakemake, Nextflow) with version control and containerization (Docker/Singularity). FAIR
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are service-orientated, proactive, thorough and able to quickly find solutions to questions and problems. You enjoy managing multiple tasks in parallel and working independently, efficiently and in a
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version control and containerization (Docker/Singularity) Statistical Modeling: Quantitative data analysis using GLMs, Bayesian methods, or mixed-effect models to interpret complex perturbation datasets