Future Tech Jobs
Future Tech Jobs
Lead translational data science initiatives using human genetics and multi-omic data to inform drug discovery decisions. Develop reproducible analysis workflows, integrate diverse biological and clinical datasets, and collaborate across multidisciplinary teams. Mentor junior scientists and translate complex findings into actionable insights for target prioritisation, biomarker nomination, and patient subgroup definition.
Lead a team of computational biologists to identify and validate novel oncology targets using integrated phenomics, transcriptomics, genomics, and proteomics data. Develop and scale methods for target discovery in oncology and immunological diseases, collaborating closely with biologists, data scientists, and engineers. Drive data strategy and present findings to stakeholders to advance drug discovery programs.
This role involves developing, qualifying, and validating molecular bioanalytical assays—such as qPCR, ddPCR, and RT-qPCR—to support clinical pharmacokinetic and pharmacodynamic studies within a GCLp-compliant environment. The scientist will work closely with cross-functional teams to ensure robust data generation, maintain regulatory compliance, and integrate emerging digital and automation technologies into workflows. A strong focus on reagent management, assay documentation, and continuous process improvement is central to the position.
This role involves developing, optimizing, and validating molecular bioanalytical assays—such as qPCR, ddPCR, and RNA isolation—to support mRNA-based clinical programs. The scientist will work within GCL0-compliant (GCLP) frameworks to generate pharmacokinetic and pharmacodynamic data, ensuring regulatory compliance and data integrity. Collaboration with cross-functional teams and adoption of digital tools and automation are key to advancing clinical trial execution and analytical processes.
Lead a team of computational biologists to integrate multi-omics data for oncology target discovery and validation, while actively contributing to data analysis and cross-functional decision-making. Develop biomarker strategies and patient stratification approaches to guide therapeutic development. Collaborate closely with biologists, chemists, and clinical teams to advance drug programs using high-dimensional datasets and scalable computational methods.
Lead translational data science initiatives using genetics and multi-omics data to generate actionable insights for target identification, biomarker development, and patient selection. Design and deliver reproducible analytical pipelines, collaborate with cross-functional teams, and mentor junior scientists in a secure, regulated environment. Work at the intersection of biology, AI/ML, and clinical development to directly influence drug discovery and early clinical translation.
Lead translational data science initiatives using genetics and multi-omics data to generate actionable insights for target identification, biomarker development, and patient selection. Design and deliver robust, reproducible analytical pipelines while collaborating with cross-functional teams in discovery and clinical translation. Mentor scientists, operationalise AI/ML methods, and ensure compliance with data governance standards in a secure research environment.
Lead translational data science initiatives by analyzing genetics and multi-omics data to generate actionable insights for drug discovery and clinical development. Design and deliver reproducible analytical pipelines, collaborate with cross-functional teams including AI/ML and bioinformatics, and translate complex data into decisions for target identification and patient selection. Mentor scientists and contribute to strategic project discussions in a multidisciplinary environment focused on advancing precision medicine.
Leads translational data strategy at a global pharmaceutical company, integrating multi-omics and AI to bridge biological discovery with clinical outcomes. The role drives computational innovation across drug discovery and development, with a focus on spatial and single-cell genomics, agentic AI systems, and biomarker-driven patient stratification. Works closely with R&D and clinical leadership to deliver actionable insights across therapeutic areas.
Leads translational data strategy by integrating multi-omics and AI-driven analytics to bridge biological discovery with clinical outcomes. Defines computational frameworks for target identification, biomarker discovery, and patient stratification across therapeutic areas. Builds strategic alliances with academic and industry partners and drives scientific innovation through publications and external engagement.
Leads translational data strategy at a global pharmaceutical company, integrating multi-omics and AI to bridge biological discovery with clinical outcomes. Defines data science vision across therapeutic areas, drives AI-driven insight generation, and aligns computational approaches with drug development priorities. Builds strategic partnerships and ensures analytical platforms deliver clinically actionable hypotheses.
