Welcome to STEMD Laboratory
BMS (Division of Biomedical Sciences )
KAUST (King Abdullah University of Science and Technology)
Overview
The Stem Cell and DIsease Laboratory focuses on the use of human embryonic stem cells (hESCs) and patient-derived induced pluripotent stem cells (iPSCs) to model the onset and progression of human disorders linked to copy number variations “in a dish.” Prof. Adamo's team developed the largest cohort of Klinefelter syndrome (karyotype 47,XXY) and high-grade X aneuploid iPSCs (karyotype 48,XXXY and 49,XXXXY). We use this unique cellular model to study the molecular dysregulations associated with X chromosome aneuploidy during the earliest stages of human development.
Professor Adamo’s team combines reprogramming, organoid derivation, and genome editing techniques with a multi-omics approach to identify the transcriptional and epigenetic signatures underlying human diseases.
.png?sfvrsn=4a5ff65c_0)
We Are Hiring a Computational/ Bioinformatics Postdoc.
A postdoctoral position is available for a bioinformatician at STEMD laboratory The team of Prof. Antonio Adamo, BMS division, at KAUST. Job Listing Detail
Position Summary The selected candidate will be responsible for leading the analysis and integration of multi-omics data, developing scalable and reproducible pipelines, and applying advanced computational methods to uncover disease mechanisms and improve patient stratification.
Major Responsibilities Design, evaluate, and implement advanced workflows for bulk RNA-seq, single-cell RNA- seq, and spatial transcriptomics to study transcriptional programs and cellular heterogeneity across large cohorts of patients with sex chromosomal. Perform comprehensive analysis and integration of multi-omics datasets (including RNA- seq, ChIP-seq, and ATAC-seq), with a focus on understanding the relationship between transcriptional regulation and epigenetic landscapes. Develop, optimize, and maintain sequencing data processing pipelines—particularly for RNA-seq and single-cell analyses—on high-performance computing (HPC) infrastructures. Identify patient-specific molecular signatures by correlating longitudinal single-cell data with clinical outcomes, contributing to improved precision in patient stratification.
Personal Requirements Competencies · PhD in Bioinformatics, Computational Biology, Systems Biology, or related field. · Proven experience in the analysis of next-generation sequencing (NGS) and other omics datasets. · Strong computational and statistical expertise, including proficiency in Unix-based systems and programming languages such as Python and R/Bioconductor, with the ability to manage and analyze large-scale biological data.
Qualifications & Experience · Demonstrated experience in building and maintaining scalable sequencing data analysis pipelines using workflow management systems such as Nextflow or Snakemake. · Hands-on expertise in the analysis of single-cell and spatial omics datasets, utilizing tools like Seurat, Scanpy, or platforms for studying spatial cell–cell interactions. · Strong background in applying machine learning and artificial intelligence methods, particularly for developing predictive models related to disease progression or patient stratification through integrated omics data. · Working knowledge of containerization technologies (e.g., Docker or Singularity) to support reproducible and portable computational workflows.
Salary and benefits package will be commensurate with the selected candidate’s qualifications and level of experience. Interested applicants are invited to submit their CV to Prof. Antonio Adamo at (antonio.adamo@kaust.edu.sa)