Post Doctoral Scientist – Human Genomics, Translational Data Science

🕒 March 26

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Xenon Seven

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

🏢 Enterprise

Artificial Intelligence • Enterprise

Xenon Seven is a company that specializes in providing AI and data solutions across various industries, including healthcare, financial services, consumer retail, high-tech, automotive, and energy utilities. With expertise in generative AI, decision support systems, predictive analytics, computer vision, robotics, and mechatronics, they support businesses in AI preparedness, exploration, transformation, and scalability. Xenon Seven works with a network of AI technologists and experts from over 20 institutions, focusing on solving complex problems and ensuring secure and seamless AI transitions for businesses. Their services aim to optimize AI infrastructure and performance while maintaining strict security standards.

📋 Description

• Apply statistical and computational approaches to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery. • Conduct rigorous analyses of large-scale population cohorts and biobank datasets to identify genetic variants and causal genes associated with disease outcomes. • Develop and implement machine learning and bioinformatics pipelines to integrate multi-omics data. • Collaborate with interdisciplinary teams, including geneticists, epidemiologists, and clinicians, to interpret findings and guide therapeutic development. • Prepare scientific reports, presentations, and publications detailing research outcomes. • Contribute to the development of novel statistical methods for analyzing high-dimensional biological data.

🎯 Requirements

• PhD in statistical genetics, bioinformatics, computational biology, biostatistics, or a related quantitative field • Qualified applicants must be authorized to work in the United States on a full-time basis. • Expertise in whole genome and whole exome sequencing analysis, proteomics, metabolomics and other molecular data analysis, and clinical outcomes research. • Strong proficiency in statistical modeling, machine learning, and high-dimensional data analysis. • Experience working with large biobank and cohort datasets (e.g., UK Biobank, All of Us, FinnGen). • Proficiency in programming languages such as R, Python, and SQL for data analysis. • Familiarity with genetic association studies, GWAS, and polygenic risk scores. • Excellent communication and collaboration skills to work effectively in cross-functional teams. • Experience in pharmaceutical or biotech industry settings. • Knowledge of functional genomics and multi-omics data integration. • Strong publication record demonstrating contributions to statistical genetics and biomarker discovery and analysis. • Prior experience in cardiometabolic research. • Prior experience with polygenic risk score models.

🏖️ Benefits

• Attractive, market-leading salary package. • Clear career advancement path with professional development opportunities.