SciLifeLab Group
Research Infrastructure Specialist in Bioinformatics (MS-based Proteomics)
SciLifeLab Group, Jackson, Mississippi, United States
Research Infrastructure Specialist in Bioinformatics (MS-based Proteomics)
SciLifeLab / Careers / Research Infrastructure Specialist in Bioinformatics (MS-based Proteomics) Do you want to contribute to top quality medical research? Computational methods and AI applied to large-scale molecular data are transforming biology – from molecular structures and cellular processes to human health and ecosystems. As part ofSciLifeLab , a unique nation-wide infrastructure and research community that combines advanced life science technologies with data and AI expertise, the Chemical Proteomics unit at the Department of Medical Biochemistry and Biophysics is looking for a Research Infrastructure Specialist in Bioinformatics with focus on MS-based proteomics. We are seeking a bioinformatician to analyse complex proteomics datasets and develop innovative tools for data processing, visualization, and generation of databases and prediction models. You will build and maintain reproducible pipelines for analysis of high-throughput chemical proteomics experiments, apply statistical and pathway analysis methods, and ensure that all datasets follow FAIR principles. The role includes supporting users of the Chemical Proteomics unit in all data-related aspects and contributing to multi-modal data integration through AI/ML approaches. This is an opportunity to shape how high-dimensional proteomics data are transformed into actionable biological insights. More specifically, you will engage in the following areas: Analyse, visualize, and interpret complex chemical proteomics datasets, including PISA, RedOX proteomics, PTMs, HDX-MS, and quantitative mass spectrometry data. Support users of the Chemical Proteomics unit in all aspects of proteomics data handling and analysis. Develop novel analysis tools, pipelines, and visualization methods tailored to chemical proteomics workflows. Apply robust statistical approaches for hit calling, differential protein quantification, and enrichment analysis. Ensure datasets are well-managed and compliant with FAIR principles. Contribute to multi-modal (multi-omics) data integration using AI/ML approaches. Eligibility requirements
PhD in Bioinformatics, Computational Biology, Systems Biology, Computer Science, Biochemistry related to proteomics and mass spectrometry, or related field. Proven methodological and research expertise Strong Python and R skills for omics data processing, QC, statistical testing, and visualization to support biological discovery Solid foundation in statistical and quantitative methods Strong communication skills and a collaborative, service-minded approach To be eligible for an employment as Research Infrastructure Specialist the applicant must have demonstrated research expertise and been awarded a PhD or a qualification from a foreign higher education institution deemed equivalent to a Swedish PhD. The applicant must also have demonstrated technological and methodological expertise. Assessment criteria
Experience or expertise in any of the following areas will be considered meritable: Use of specialized tools for data analysis, statistical testing, and visualization for MS-based proteomics datasets. Knowledge of website building (on Django, Rshiny, etc.) Specialized knowledge in MS-based proteomics: understanding of peptide-spectrum matching, FDR estimation, etc. Knowledge of statistical and quantitative methods for protein and peptide level analysis, including normalization, missing-value handling, differential quantification, clustering and correlations. Ability in specialized technical tools for proteomics, developing and maintaining reproducible pipelines for mass spectrometry or proteomics workflows including database search engines (MaxQuant, Proteome Discoverer, Peaks Studio, DIA-NN, HDX-Examiner, etc), MS RAW data analysis software (Xcalibur, Freestyle, etc.). Proficiency in protein-centric pathway analysis, enrichment, and network analysis using tools such as ReactomePA, clusterProfiler, Cytoscape, and databases including Reactome, KEGG, and GO. Multi-modal data integration: combining different proteomics modalities, and complementary data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. Familiarity with proteomics-specific public repositories (e.g., PRIDE) and metadata standards, ensuring FAIR data management. After an overall assessment of the expertise and merits of the applicants in relation to the subject area, Karolinska Institutet will determine which of them has the best potential to contribute to a positive development of the activities at KI. What do we offer?
Karolinska Institutet is one of the world’s leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet is a state university, which entitles to several benefits such as extended holiday and generous occupational pension. Employees also have access to our modern gym for free and receive reimbursements for medical care. The workplace will be at Biomedicum, hosting top-ranked research groups and infrastructure facilities in the KI Solna Campus, near to the SciLifeLab national infrastructure, also hosting research groups and facilities. The work environment is a creative, international, and inspiring environment with wide-ranging expertise and interest. Chemical Proteomics encourages personal and professional growth through access to courses, workshops, conferences, and specialized training. We foster a flexible and supportive work culture, emphasizing collaboration, mentoring, and peer learning. While this position is initially limited to one year, it is anticipated to be advertised to be renewed and made permanent in the future, and the current holder will be encouraged to apply, contingent on strong performance during the first year. The deadline for application is 2025-10-31. Applications must be submitted through the Varbi recruitment system. Want to make a difference? Join us and contribute to better health for all!
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SciLifeLab / Careers / Research Infrastructure Specialist in Bioinformatics (MS-based Proteomics) Do you want to contribute to top quality medical research? Computational methods and AI applied to large-scale molecular data are transforming biology – from molecular structures and cellular processes to human health and ecosystems. As part ofSciLifeLab , a unique nation-wide infrastructure and research community that combines advanced life science technologies with data and AI expertise, the Chemical Proteomics unit at the Department of Medical Biochemistry and Biophysics is looking for a Research Infrastructure Specialist in Bioinformatics with focus on MS-based proteomics. We are seeking a bioinformatician to analyse complex proteomics datasets and develop innovative tools for data processing, visualization, and generation of databases and prediction models. You will build and maintain reproducible pipelines for analysis of high-throughput chemical proteomics experiments, apply statistical and pathway analysis methods, and ensure that all datasets follow FAIR principles. The role includes supporting users of the Chemical Proteomics unit in all data-related aspects and contributing to multi-modal data integration through AI/ML approaches. This is an opportunity to shape how high-dimensional proteomics data are transformed into actionable biological insights. More specifically, you will engage in the following areas: Analyse, visualize, and interpret complex chemical proteomics datasets, including PISA, RedOX proteomics, PTMs, HDX-MS, and quantitative mass spectrometry data. Support users of the Chemical Proteomics unit in all aspects of proteomics data handling and analysis. Develop novel analysis tools, pipelines, and visualization methods tailored to chemical proteomics workflows. Apply robust statistical approaches for hit calling, differential protein quantification, and enrichment analysis. Ensure datasets are well-managed and compliant with FAIR principles. Contribute to multi-modal (multi-omics) data integration using AI/ML approaches. Eligibility requirements
PhD in Bioinformatics, Computational Biology, Systems Biology, Computer Science, Biochemistry related to proteomics and mass spectrometry, or related field. Proven methodological and research expertise Strong Python and R skills for omics data processing, QC, statistical testing, and visualization to support biological discovery Solid foundation in statistical and quantitative methods Strong communication skills and a collaborative, service-minded approach To be eligible for an employment as Research Infrastructure Specialist the applicant must have demonstrated research expertise and been awarded a PhD or a qualification from a foreign higher education institution deemed equivalent to a Swedish PhD. The applicant must also have demonstrated technological and methodological expertise. Assessment criteria
Experience or expertise in any of the following areas will be considered meritable: Use of specialized tools for data analysis, statistical testing, and visualization for MS-based proteomics datasets. Knowledge of website building (on Django, Rshiny, etc.) Specialized knowledge in MS-based proteomics: understanding of peptide-spectrum matching, FDR estimation, etc. Knowledge of statistical and quantitative methods for protein and peptide level analysis, including normalization, missing-value handling, differential quantification, clustering and correlations. Ability in specialized technical tools for proteomics, developing and maintaining reproducible pipelines for mass spectrometry or proteomics workflows including database search engines (MaxQuant, Proteome Discoverer, Peaks Studio, DIA-NN, HDX-Examiner, etc), MS RAW data analysis software (Xcalibur, Freestyle, etc.). Proficiency in protein-centric pathway analysis, enrichment, and network analysis using tools such as ReactomePA, clusterProfiler, Cytoscape, and databases including Reactome, KEGG, and GO. Multi-modal data integration: combining different proteomics modalities, and complementary data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. Familiarity with proteomics-specific public repositories (e.g., PRIDE) and metadata standards, ensuring FAIR data management. After an overall assessment of the expertise and merits of the applicants in relation to the subject area, Karolinska Institutet will determine which of them has the best potential to contribute to a positive development of the activities at KI. What do we offer?
Karolinska Institutet is one of the world’s leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet is a state university, which entitles to several benefits such as extended holiday and generous occupational pension. Employees also have access to our modern gym for free and receive reimbursements for medical care. The workplace will be at Biomedicum, hosting top-ranked research groups and infrastructure facilities in the KI Solna Campus, near to the SciLifeLab national infrastructure, also hosting research groups and facilities. The work environment is a creative, international, and inspiring environment with wide-ranging expertise and interest. Chemical Proteomics encourages personal and professional growth through access to courses, workshops, conferences, and specialized training. We foster a flexible and supportive work culture, emphasizing collaboration, mentoring, and peer learning. While this position is initially limited to one year, it is anticipated to be advertised to be renewed and made permanent in the future, and the current holder will be encouraged to apply, contingent on strong performance during the first year. The deadline for application is 2025-10-31. Applications must be submitted through the Varbi recruitment system. Want to make a difference? Join us and contribute to better health for all!
#J-18808-Ljbffr