Job Description Summary

Job Description

Your responsibilities will include to

• Leverage data from repositories of clinical data to identify new therapeutic targets and generate testable hypotheses for validation in preclinical models.
• Connect multimodal clinical and preclinical data (e.g., genomics, proteomics, imaging, histology) to inform early discovery and generate a deep understanding of disease states, disease progression and patient stratification.
• Contribute to our drug discovery engine by designing, using, and improving data science tools to derive new insights from multimodal/multiomic datasets.
• Collaborate with experimental and computational scientists to generate hypotheses, design experiments, analyze and interpret data.
• Communicate data and analyses to broad, multidisciplinary audiences.

Role Requirements

• You hold a Master's degree or a PhD in a quantitative field such as computational biology, bioinformatics, data science, mathematics, statistics, or physics. Experience working in life science is highly desirable.
• You can communicate complex data-science concepts in digestible terms to diverse scientific audiences.
• Hands-on expertise in using patient and/or clinical data to generate hypotheses is highly desirable.
• You have experience identifying, curating, and integrating large-scale multimodal and/or real world evidence data.
• You can demonstrate scientific curiosity, initiative, and learning agility.
• You can work as part of an interdisciplinary team.
• You have expertise working in Linux high-performance computing and cloud environments.
• You have expertise in scripting programming languages, Python and/or R, and you can demonstrate best practices in building custom scientific software (version control, testing, documentation).
• Experience developing machine-learning models using biological datasets is a plus.

Skills Desired