Are you an experienced computational biologist who wants to leverage cutting-edge multi-omics technologies, advanced computational approaches and machine learning to transform women's health? At the Carlos Simón Foundation, we work at the forefront of reproductive medicine and women’s health, and we are looking for a scientist to lead the computational work of our flagship project, DECIDUA. As Senior Computational Biologist, you will lead advanced bioinformatics, machine-learning and computational modeling analyses, develop novel analytical methods, and contribute to the Foundation's broader strategy for the management, integration and reuse of omics data. The Carlos Simón Foundation is seeking an experienced Senior Computational Biologist to lead advanced computational analyses across major research programs in reproductive and women’s health. The successful candidate will play a key role in DECIDUA, a flagship research project integrating single-cell, spatial, multi-omic and liquid-biopsy data, while contributing to the Foundation's broader computational research strategy. Lead the computational strategy and execution of DECIDUA, setting priorities, milestones and quality standards together with the Principal Investigator. Identify cell states, molecular programs and biological signatures through advanced computational and integrative analyses. Work closely with biologists, clinicians and senior investigators; mentor junior computational and technical staff; PhD in Bioinformatics, Computational Biology, Statistics, Computer Science or another quantitative discipline, plus 5+ years of relevant postdoctoral or industry experience (exceptional MSc candidates considered). Proven track record analyzing large-scale sc/snRNA-seq data, including multi-dataset integration and batch correction (e.g., Deep understanding of several areas of modern NGS bioinformatics (bulk RNA-seq, ATAC-seq, spatial transcriptomics, multi-omic integration)



and experience in trajectory inference or network-based modeling. Strong foundation in biostatistics and machine learning (penalized regression, tree-based and boosting models, nested cross-validation, calibration, SHAP), with experience building predictive models on clinical or biomarker data. Fluency in R (Bioconductor, RMarkdown) and Python (Pandas, NumPy); proficiency with Linux and/or cloud HPC environments and shell scripting. Solid understanding of molecular and cell biology. Demonstrated ability to lead analytical projects and mentor junior scientists. Reproducible pipelines (Snakemake or Nextflow), good software practices and fluency with git; experience in a lower-level language (Rust, C++, Java). Boolean networks, MaBoSS, ODE-based models) and hybrid mechanistic–machine-learning (“digital twin”) approaches. Experience with plasma cell-free RNA, liquid-biopsy or other transcriptomic biomarker data from clinical cohorts. Knowledge of endometrial, reproductive or placental biology. Personal Qualities Excellent communication

skills:
able to explain algorithms and statistical methods to non-technical stakeholders such as clinicians and biologists. Ability to network, influence and collaborate, balancing the needs of multiple stakeholders. A leadership role with scientific ownership of the computational program of a flagship project in women’s health research. hybrid work mode. Opportunities to publish, present internationally, supervise junior researchers and build a long-term career within the Foundation. The Foundation is part of the INCLIVA Health Research Institute, jointly established with the University of Valencia and the Hospital Clínico of Valencia. We are a multidisciplinary team of more than 40 professionals working to create a world in which women's health pathologies affecting the uterus are no longer a barrier to quality of life and reproductive desire. Our main activity is biomedical research in reproductive medicine and women’s health, and its clinical application. #

📌 Senior Computer Biologist (España)
🏢 Carlos Simon Foundation for Research in Women's Health
📍 España