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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in analyzing single-cell, spatial, and multiomic datasets, with strong programming skills in Python and experience in building reproducible analytical workflows. Proficient in integrating diverse biological data modalities and applying machine learning approaches to derive actionable insights.
Highest-signal resume keywords
PhD In Computational BiologySingle-Cell Data AnalysisSpatial Omics Data AnalysisPython ProgrammingMachine Learning Approaches
ATS Keywords
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Hard Skills
Single-Cell Data AnalysisSpatial Omics Data AnalysisTranscriptomics AnalysisMultiomic Data AnalysisAnalytical Workflow DevelopmentData IntegrationMachine LearningBiological Data Analysis
Soft Skills
Strong Communication SkillsCollaboration SkillsMentoring
Tools & Technologies
ScanpySeuratSquidpyGitHubGitLab
Industry Keywords
Computational BiologyBioinformaticsGenomicsBiomedical SciencesTranslational Science
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Design and execute analyses of single-cell, spatial and multiomic datasets
- Transform complex biological data into actionable target discovery insights
- Build and maintain reproducible analytical workflows and pipelines
- Integrate transcriptomic, proteomic, metabolomic and imaging datasets
- Investigate vascular, immune and tissue-resident cell populations in complex disease environments
- Generate evidence supporting target prioritisation and validation strategies
- Partner with biology, translational science, clinical and AI teams
- Evaluate emerging computational technologies and analytical approaches
- Help shape biomarker strategies and patient stratification approaches
- Mentor colleagues and champion computational best practices
- Communicate findings through presentations, publications and scientific collaborations
Requirements
What you’ll need- PhD in Computational Biology, Systems Biology, Bioinformatics, Genomics, Biomedical Sciences, Medicine or a related discipline
- Strong hands-on experience analysing single-cell datasets
- Strong hands-on experience analysing spatial omics datasets
- Strong hands-on experience analysing transcriptomics and multiomic data
- Strong programming skills in Python
- Experience building robust and reproducible analytical workflows
- Familiarity with Scanpy, Seurat, Squidpy or similar analytical frameworks
- Experience applying machine learning approaches to biological datasets
- Experience integrating different biological data modalities
- Familiarity with GitHub, GitLab or equivalent version-control practices
- Strong communication and collaboration skills
- Fluent English
Benefits
Comp & perks- Annual bonus may be offered
- Eligibility to participate in a share based long term incentive program
- Competitive compensation and benefits
- Access to state-of-the-art computational, spatial and single-cell technologies
- Hybrid working arrangements
- Strong commitment to learning, growth and development
- Collaborative environment where biology, AI and data science intersect
- Urlaubsgeld and additional days off
- Altersvorsorge
- Health & Wellbeing Benefits
- Bezahlte Elternzeit und Pflegezeit