I am a Multi-Omics Bioinformatician with over a decade of experience in genomics, transcriptomics, epigenomics, single-cell biology, and computational systems analysis across diverse biological domains. Having conducted research and supported projects in the UK, Middle East, and Denmark, I am committed to ensuring that my work delivers real scientific and societal impact. I have authored peer-reviewed articles across multiple applications and advanced data-driven analytics. I collaborate closely with researchers, clinicians, and industry partners to develop robust, reproducible workflows and to translate complex multi-omics datasets into meaningful biological insights. I am currently a Multi-Omics Bioinformatician in the Department of Animal and Veterinary Sciences (ANIVET) at Aarhus University, supporting large-scale  genomics, transcriptomcis, epigenomics, phenomics, and integrative multi-omics research.

My research focuses on developing and applying integrative multi-omics approaches to uncover molecular mechanisms across diverse biological systems, including complex traits, livestock, cancer, etc. It also examines broader aspects of data quality, reproducibility, and computational robustness in high-dimensional genomics and single-cell data. In my current work at ANIVET, I collaborate with researchers, veterinarians, and industry partners to build reliable pipelines and analytical frameworks that support large-scale  genomics, transcriptomics, epigenetics, phenomics studies. In doing so, I draw on over a decade of expertise in bioinformatics, HPC workflows, and multi-omics integration to help research teams navigate rapidly advancing genomic technologies and translate complex datasets into actionable insights.

A full tenured Multi-Omics Bioinformatician supporting research teams by enabling high-quality, reproducible multi-omics research through strong interdisciplinary collaboration. Provides guidance in transforming complex datasets into meaningful scientific insights and develops scalable, transparent bioinformatics workflows that ensure analytical rigor, reproducibility, and consistency across large research projects. A key part of the role involves building and maintaining computational pipelines on HPC environments using Nextflow and Singularity/Apptainer. Routinely supports genomics, transcriptomics, epigenomics, scRNA-seq and ATAC-seq, spatial transcriptomics, and phenomics data, ensuring access to robust and reliable analytical tools aligned with scientific objectives.

In addition to pipeline development, the role includes designing strategies for integrative multi-omics analysis. This involves combining datasets across platforms and modalities—such as linking gene expression with genomic variants, integrating single-cell and bulk datasets, constructing co-expression and regulatory networks, and analysing complex traits in phenomics studies. These integrative approaches help uncover biological mechanisms and provide a systems-level understanding that strengthens downstream discoveries. Works closely with interdisciplinary teams spanning animal science, computational biology, veterinary sciences, and clinical genomics. Responsibilities include advising researchers on study design, analytical workflows, data transformation, statistical modelling, and best practices in reproducible research.