Senior Bioinformatics Scientist

1w1 week ago

CatalYm

DE · Full-time · €75,000 – €110,000

About this role

As a Senior Scientist Bioinformatics, lead the analysis and integration of transcriptomic and multi-omics data, including RNA-seq and spatial transcriptomics, from clinical trial samples and public datasets. Translate complex data into actionable biological insights supporting biomarker discovery and patient stratification. Collaborate closely with cross-functional teams to advance clinical development.

Analyze and interpret complex datasets like bulk and single-cell RNA-seq, spatial transcriptomics, proteomics, metabolomics, and ctDNA. Integrate data from sources such as TCGA and GEO to generate biologically meaningful insights. Develop, implement, and optimize computational pipelines for high-throughput sequencing data processing.

Ensure high data quality through robust quality control, normalization, and reproducible workflows. Organize, manage, and maintain large-scale datasets while documenting methods for transparency. Provide scientific leadership by building structured research plans aligned with company strategy.

Work closely with scientists, clinicians, and cross-functional teams to interpret data and inform experimental design. Communicate findings via presentations, reports, and scientific publications. Contribute to biomarker discovery and clinical development in a dynamic biotech environment.

Join a company at the forefront of innovative cancer therapies with a promising clinical-stage oncology program. Stay current with bioinformatics advances and apply emerging technologies. Drive projects from hypothesis generation to actionable conclusions.

Requirements

Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field
Proficient in programming languages such as Python, R, or similar
Experienced with bioinformatics tools and workflows for bulk and single-cell RNA-seq and spatial transcriptomics analysis (e.g., STAR, HISAT2, DESeq2, Seurat, Scanpy, Squidpy)
Hands-on experience with bulk and single-cell RNA-seq and spatial transcriptomics, including data visualization approaches
Strong understanding of statistical methods for high-dimensional data analysis
Proven ability to work with and derive insights from large-scale biological datasets
Experience in immunology, preferably with a focus on tumor immunology
Strong problem-solving skills and critical thinking with a structured and hypothesis-driven approach

Responsibilities

Analyze and interpret complex transcriptomic and multi-omics datasets, including bulk and single-cell RNA-seq, spatial transcriptomics, proteomics, metabolomics, and ctDNA analysis
Integrate data from diverse sources, including publicly available datasets like TCGA and GEO, and clinical trial samples
Develop, implement, and optimize computational pipelines for processing and analysis of high-throughput sequencing data
Ensure high data quality through robust quality control, normalization, and reproducible analysis workflows
Organize, manage, and maintain large-scale datasets in a structured and accessible manner
Provide scientific leadership for assigned research projects by building structured research plans and driving execution
Collaborate closely with scientists, clinicians, and cross-functional teams to interpret data and inform experimental design
Communicate findings effectively through presentations, reports, and contributions to scientific publications

Benefits

Opportunity to contribute to the advancement of a promising clinical-stage oncology program
Role within a dynamic biotech company at the forefront of innovative cancer therapies