Bioinformatician (f/m/d)

Bioinformatician (f/m/d)

Multi-Omics Data analysis and Integration (COMBI-OMICS)

The following full-time (39.5 h/week) position in scientific bioinformatics is available at Heidelberg University, to begin on January 01, 2027:

Bioinformatician (f/m/d)

Multi-Omics Data analysis and Integration (COMBI-OMICS)

Do you enjoy turning complex omics data into robust, reproducible workflows and biologically meaningful insights?

Do you like working at the interface between experimental Core Facilities, computational methods and biomedical research?

We are looking for a highly motivated, collaborative and service-oriented bioinformatics scientist to establish reusable analysis workflows and scientific support for integrated multi-omics projects across the Heidelberg life science campus.

COMBI-OMICS (Core-Facility Bioinformatics Integration for Multi-Omics Analyses) is a joint initiative of the Metabolomics Core Technology Platform (MCTP), the Expression & Spatial Profiling (ESP) Core Facility, the Core Facility for Mass Spectrometry & Proteomics, and the Deep Sequencing Core Facility. The position will be embedded between these experimental platforms and the emerging University Bioinformatics Core Facility, creating a professional bridge from data generation to integrative biological interpretation.

Your tasks:

You develop, implement and maintain reproducible, modular bioinformatics workflows for metabolomics, proteomics/phosphoproteomics, transcriptomics, targeted expression and spatial profiling data using Nextflow/nf-core and community best practices

Reuse, customize and contribute to the nf-core ecosystem by adapting existing modules and developing new components where required based on existing R- or python packages

Establish harmonized metadata standards, project intake procedures and cross-platform quality control together with the participating Core Facilities

You create a structured toolbox for quality control, preprocessing, statistical analysis, multi-omics integration and biological interpretation, including matched-sample, pathway-level, prior-knowledge-informed, network-based and multi-view approaches

You translate workflows into automated, user-facing reports with clear visualizations, interpretation, documentation and transparent decision points

You advise and support researchers from study design, feasibility and data handover through statistical analysis and integrated biological interpretation

You contribute to selected pilot and user projects, SOPs and training materials, as well as scientific publications and third-party funding applications

Requirements:

PhD degree in bioinformatics, computational biology, systems biology, biostatistics, data science or a comparable life-science or quantitative discipline

Strong programming skills in R and/or Python, and experience developing reproducible, maintainable computational workflows using modern software development practices (e.g. Git, testing, documentation, package management)

Experience in developing or maintaining workflow management systems such as Nextflow (ideally within the nf-core ecosystem) or comparable workflow frameworks (e.g. Snakemake, WDL, CWL)

Demonstrated experience analysing high-throughput omics data, with expertise spanning at least two molecular data types (e.g. metabolomics, proteomics, phosphoproteomics, transcriptomics or spatial omics)

A good understanding of experimental design, batch effects, biological variation and the challenges of biomedical or clinica