Jessica Nordlund
Associate Professor & Research Group Leader at Uppsala University
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Positions (1)
Jessica Nordlund
Uppsala University
7 months ago
Uppsala University is seeking a technology-driven bioinformatician to join the Data Operations group at the SciLifeLab National Genomics Infrastructure (NGI) node in Uppsala. This permanent, full-time position is based in the Department of Medical Sciences, a large clinical department with a strong research profile in genomics, molecular biology, and clinical research. The successful candidate will work at the interface of bioinformatics and IT, supporting large-scale sequencing (NGS), SNP genotyping, and proteomics services for academia, industry, and international users. The role involves designing, developing, and maintaining open-source systems for processing and analyzing large-scale genomics data, managing data on high-security compute clusters, automating data handling, and integrating systems for laboratory tracking, document management, and KPI visualization. The position also includes developing and supporting internal systems such as LIMS and DevOps solutions (e.g., Ansible, GitLab), and collaborating with Uppsala University IT, UPPMAX, and other SciLifeLab units. Tools and systems used include Arteria, CheckQC, nf-core pipelines, and Nextflow. Applicants must have a university degree in bioinformatics, computer science, IT, or a related field, with at least three years of documented work experience in bioinformatics-related systems development. Required skills include proficiency in Python or a similar programming language, experience with pipeline development (e.g., Nextflow), knowledge of molecular biology and genetics, experience with Git, and excellent English communication skills. Additional valued qualifications include experience with computer clusters, virtualized environments (Docker/Apptainer), software deployment and automation (Ansible, CI/CD), modern software engineering practices, LIMS development, data management, information security, Agile methodologies, and working in quality-assured environments (ISO 17025/27001). A doctoral degree in bioinformatics or a related area is considered an additional qualification. Swedish language skills are a plus. The position offers a stimulating and forward-looking environment, with opportunities to work closely with cutting-edge research and a multidisciplinary team. Uppsala University provides individual salary, standard university benefits, and a supportive workplace recognized for HR Excellence in Research. The application deadline is 13 March 2026, and applications should be submitted through the university's recruitment system, including a CV, documentation of competence, and answers to application questions in lieu of a personal letter. For further information, contact Kristina Larsson (head of Data Operations) or Ulrika Liljedahl (head of unit SNP&SEQ). For more details, visit the official job posting and departmental websites. The position may be subject to security vetting.
7 months ago
Articles (11)
Functional precision medicine (FPM) aims to optimize patient-specific drug selection based on the unique characteristics of their cancer cells. Recent advancements in high throughput ex vivo drug profiling have accelerated interest in FPM. Here, we present a proof-of-concept study for an integrated experimental system that incorporates ex vivo treatment response with a single-cell gene expression output enabling barcoding of several drug conditions in one single-cell sequencing experiment. We demonstrate this through a proof-of-concept investigation focusing on the glucocorticoid-resistant acute lymphoblastic leukemia (ALL) E/R+ Reh cell line. Three different single-cell transcriptome sequencing (scRNA-seq) approaches were evaluated, each exhibiting high cell recovery and accurate tagging of distinct drug conditions. Notably, our comprehensive analysis revealed variations in library complexity, sensitivity (gene detection), and differential gene expression detection across the methods. Despite these differences, we identified a substantial transcriptional response to fludarabine, a highly relevant drug for treating high-risk ALL, which was consistently recapitulated by all three methods. These findings highlight the potential of our integrated approach for studying drug responses at the single-cell level and emphasize the importance of method selection in scRNA-seq studies. Finally, our data encompassing 27 327 cells are freely available to extend to future scRNA-seq methodological comparisons.
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2024
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2023
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2023
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2023
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2022
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2022
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2022
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2021
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2021
Collaborators (16)
Vladimir Lazarevic
Lund University
Laura Oksa
University of Tampere
Marta Lomnytska
Uppsala University Hospital
Tobias Sjöblom
Professor at Uppsala University
Uppsala University
Adam Ameur
Uppsala University
Veronica Rendo
Uppsala University
Arja Harila-Saari
Professor of paediatrics
Uppsala University
Markus Ringnér
Lund University
Andreas Scherer
Institute for Molecular Medicine Finland
Gunnel Nordmark
Associate Professor, adjunct lecturer
Uppsala University
Ann‐Christine Syvänen
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K Sundfeldt
University of Gothenburg, Sahlgrenska Academy
Richard Rosenquist
Karolinska Institutet
Merja Heinäniemi
Professor at University of Eastern Finland
University of Eastern Finland
Mattias Andersson
Associate professor
University of Gothenburg
Ting Gong
University of Hawaii
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