Lead multiomics integration and biomarker discovery to support precision medicine strategies across discovery and clinical development.
Locations (2)
Madrid, Spain, Spain
Barcelona, Spain, Spain
Compensation
The anticipated base pay range for this position is:
€44,000.00 - €70,840.00
Responsibilities
Develop, implement, and apply integrative multiomics frameworks to identify biomarkers and patient subtypes relevant to xTA discovery and clinical precision strategies.
Integrate diverse data modalities, including genomics, transcriptomics, proteomics, single-cell/spatial omics, QTLs, imaging, and clinical/real-world data, to characterize disease heterogeneity.
Design patient stratification and subtyping approaches that link molecular signatures to disease mechanisms, prognosis, and treatment response.
Quantify and prioritize biomarker evidence supporting target engagement, pharmacodynamic response, and patient selection.
Apply systems biology, network analysis, and statistical/ML methods to connect targets, pathways, biomarkers, and clinical phenotypes.
Requirements
PhD in Computational Biology, Bioinformatics, Systems Biology, Genetics, Biostatistics, or a related quantitative life science discipline, with relevant postdoctoral or industry experience; or a master’s degree in a related field with at least 4 years of relevant experience.
Develop and apply multiomics integration methods and frameworks for biomarker identification and patient subtyping to enable precision medicine strategies across disease areas.
Locations (2)
Madrid, Madrid, Spain
Barcelona, Catalonia, Spain
Compensation
The anticipated base pay range for this position is:
€44,000.00 - €70,840.00
Responsibilities
Develop, implement, and apply integrative multiomics frameworks to identify biomarkers and patient subtypes relevant to xTA discovery and clinical precision strategies.
Integrate diverse data modalities, including genomics, transcriptomics, proteomics, single-cell/spatial omics, QTLs, imaging, and clinical/real-world data, to characterize disease heterogeneity.
Design patient stratification and subtyping approaches that link molecular signatures to disease mechanisms, prognosis, and treatment response.
Quantify and prioritize biomarker evidence supporting target engagement, pharmacodynamic response, and patient selection.
Apply systems biology, network analysis, and statistical/ML methods to connect targets, pathways, biomarkers, and clinical phenotypes.
Requirements
PhD in Computational Biology, Bioinformatics, Systems Biology, Genetics, Biostatistics, or a related quantitative life science discipline
Master’s degree in a related field with at least 4 years of relevant experience