Embl
BiologicalDataScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Biological Data Scientist at Embl. Skills: Bioinformatics, Data analysis, Scientific computing, Programming. Conduct independent research projects. Engage in scientific collaborations”
Industry & Context.
Experience with compute clusters, Experience with pipelines of batch jobs
What They're Looking For.
Must Have
Ph. D. degree or equivalent working experience in bioinformatics, computational biology, biostatistics, or related subjects, Substantial experience in scientific computing and/or software development, Experience with large-scale data management and analysis, Advanced skills in a high level programming language (>2 years of experience), Experience in data analysis, statistics and visualization, e. g. in Python, R or MatLab, Ability to work independently and in a team, Ability to work at the interface between life sciences and informatics, Willingness to learn new skills and programming languages, Good communication, interpersonal and English language skills
Nice to Have
Experience with metagenomics and metatranscriptomics analyses, Familiarity with high-throughput sequencing, proteomics and/or metabolomics data acquisition and analysis, Experience in multi-omics data integration, Familiarity with genome-scale metabolic modelling, Familiarity with machine learning methods and approaches, Experience in mathematical modeling of dynamic systems (e. g. MatLab SimBiology, Python ModSimPy), Experience with compute clusters (e. g. SGE, slurm) and pipelines of batch jobs (e. g. Snakemake, Luigi), Dry- or wet-lab experience in microbial sciences or microbiome research
What You'll Do.
Conduct independent research projects
Engage in scientific collaborations
Provide bioinformatics and data analysis support
Develop and maintain bioinformatics software
Adapt existing code and pipelines
Provide programming and statistics support
Handle large scale data
Establish infrastructure and data management systems
How You'll Work.
Team & Collaboration
Engagement in scientific collaborations; Programming and statistics support to group members; Ability to work in a team; Work at the interface between life sciences and informatics
Communication Scope
Good communication skills; Interpersonal skills; English language skills
Full Job Description
Your role Your role involves conducting own independent research projects, engagement in scientific collaborations, as well as generic bioinformatics and data analysis support of the group. Research questions include, but are not limited to, microbial functional genomics, modelling metabolic interactions, and building predictive models of microbiome functions. Your tasks will include development and maintenance of bioinformatics software for different research projects, adaptation of existing code and pipelines, and providing programming and statistics support to the group members. The position involves large scale data handling from mass-spectrometry and sequencing experiments (metabolomics, proteomics, NGS), and establishing infrastructure and data management systems within the group and externally. You have -a Ph.D. degree or equivalent working experience in bioinformatics, computational biology, biostatistics, or related subjects -substantial experience in scientific computing and/or software development -experience with large-scale data management and analysis -advanced skills in a high level programming language (>2 years of experience) -experience in data analysis, statistics and visualization, e.g. in Python, R or MatLab -ability to work independently and in a team, and at the interface between life sciences and informatics -willingness to learn new skills and programming languages as project require -good communication, interpesonal and English language skills You may also have -Experience with metagenomics and metatranscriptomics analyses -Familiarity with high-throughput sequencing, proteomics and/or metabolomics data acquisition and analysis -Experience in multi-omics data integration -Familiarity with genome-scale metabolic modelling -Familiarity with machine learning methods and approaches -Experience in mathematical modeling of dynamic systems (e.g. MatLab SimBiology, Python ModSimPy) -Experience with compute clusters (e.g. SGE, slurm) and pipelines o
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