Required Qualifications Ph.D. or M.Sc. in Bioinformatics, Computational Biology, Data Science, or a related field . Strong experience in single-cell transcriptomics (scRNA-seq, scATAC-seq, etc.) and/or spatial omics analysis. Proficiency in R and Python for bioinformatics and statistical analysis. Hands-on experience with nf-core pipelines and Nextflow . Experience working with high-performance computing (HPC) environments and cloud-based solutions. Familiarity with open-source bioinformatics tools for single-cell analysis (e.g., Seurat, Scanpy, Cell Ranger, Squidpy). Solid understanding of machine learning approaches applied to biological data. Ability to work both independently and as part of a collaborative, interdisciplinary team. Strong problem-solving skills and attention to detail. Preferred Qualifications Experience with visualization techniques for single-cell and spatial omics data. Experience with multi-omics integration (e.g., single-cell RNA-seq + ATAC-seq/ ChIP-seq). Familiarity with database management and workflow automation. Knowledge of statistical modeling and network-based analysis. Contributions to open-source bioinformatics projects.