Bioinformatician – Multi-Omics Data Analyst

The MultiOmics Unit within the Diagnostics and Clinical Laboratories Division at Sheba Medical Center is seeking an experienced, hands-on Bioinformatician. In this full-time role, you will lead advanced analyses across a diverse range of sequencing data types and spearhead the development of reproducible analysis pipelines. This position offers a unique opportunity to combine independent research with high-impact clinical and academic collaborations at the forefront of medical diagnostics.

Key Responsibilities

• Analysis of bulk RNA-seq data: preprocessing, alignment, quantification, differential expression (DE), and pathway/enrichment analysis.
• Single-cell and single-nucleus analysis (scRNA-seq / snRNA-seq): QC, normalization, integration, clustering, cell-type annotation, trajectory inference, and cell–cell communication analysis.
• Processing and analysis of Oxford Nanopore (long-read) data: long-read alignment, isoform/transcript-level analysis, structural variant detection, and direct RNA sequencing.
• Methylation / epigenomics analysis: WGBS / RRBS, as well as methylation calling from Nanopore data (5mC/5hmC), differentially methylated region (DMR) detection, and integration with expression data.
• Multi-omics integration of transcriptomic, epigenomic, and genomic data.
• Development, documentation, and maintenance of automated, reproducible pipelines (Snakemake / Nextflow) on HPC infrastructure.
• Data visualization, biostatistics, and scientific writing (contributing to papers, posters, and grant applications).

Required Qualifications

• M.Sc. or Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related field.
• Demonstrated experience analyzing at least two of the following: RNA-seq, single-cell, long-read sequencing, methylation.
• Strong proficiency in Python and/or R, including common libraries (Scanpy / Seurat, DESeq2 / edgeR, etc.).
• Comfortable working in a Linux/Unix command-line environment, including HPC clusters and job schedulers (e.g., SLURM).
• Familiarity with standard bioinformatics tools (STAR, minimap2, samtools, bedtools, etc.).
• Version control with Git.

Strong Advantages

• Experience with Nanopore sequencing and methylation calling from long reads.
• Familiarity with workflow managers (Snakemake / Nextflow) and containers (Docker / Singularity).
• Background in machine learning / deep learning in a genomic context.
• Experience working with clinical data and public databases (TCGA, GTEx, UK Biobank, etc.).
• Experience with cloud computing and/or GPU-based workflows.
• Experience with 10x data analysis.

What We Offer

• Work at the forefront of genomic research, with access to unique datasets and advanced computing infrastructure.
• A collaboration-rich clinical-research environment with partners in Israel and abroad.