The Bioinformatician will be responsible for leveraging multi-omics data, with a focus on transcriptomics, proteomics and integrative omics, to build a predictive platform for safety assessment in drug development. They will play a crucial role in advancing our understanding of predictive safety markers and contributing to the development of innovative predictive models.

Responsibilities: Work closely with cross-functional teams to develop and implement computational strategies for analyzing and integrating multi-omics data, with a specific focus on proteomics and other relevant omics datasets. Use statistical and machine learning approaches to identify predictive safety markers and build robust predictive models for safety assessment in drug development. Contribute to the design and implementation of bioinformatics pipelines for processing, quality control, and analysis of multi-omics data. Collaborate with experimental scientists to interpret omics data in the context of safety assessment and provide actionable insights to guide decision-making in drug development. Stay abreast of the latest developments in bioinformatics, multi-omics, and predictive modeling, and apply cutting-edge methodologies to enhance predictive safety assessment capabilities. Requirements: A Ph.D. or equivalent experience in bioinformatics, computational biology, or a related field with a focus on multi-omics data analysis. Proven expertise in analyzing and integrating multi-omics data, particularly in the context of proteomics, transcriptomics and metabolomics, with the potential for omics datatypes relevant to safety assessment. Proficiency in programming languages such as R or Python, and experience with bioinformatics tools and databases commonly used in omics data analysis. Strong understanding of statistical methods, machine learning approaches, and data visualization techniques for omics data analysis and predictive modeling. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.

Desirable: Experience working in the pharmaceutical or biotechnology industry, with a focus on safety assessment or drug development. Familiarity with regulatory requirements and industry standards related to safety assessment and predictive modeling in drug development. Publications or contributions to the development of predictive models or bioinformatics pipelines in the context of multi-omics data analysis.