General Summary: 

The Predictive and Investigative Safety Assessment (PISA) group is seeking a candidate with a strong desire to be part of a highly innovative company aimed at transforming the lives of people with serious diseases, their families, and society. This role will support preclinical safety assessment for the global research portfolio from target selection through the lead optimization phase. This individual will work in a close-knit team and leverage laboratory automation and computation to plan, execute, analyze, and derive insights from mechanistic and phenotypic screening assays designed to evaluate the safety of new candidate molecules. The individual will advance the group’s experimental and computational capabilities as an integral part of the overall discovery toxicology strategy at Vertex. In addition, the individual will contribute to the evolution and implementation of the Preclinical Safety Assessment (PSA) and the broader Preclinical Sciences (PCS) data strategies.   

The ideal candidate will have both a wet-laboratory and computational skillset that will enable them to maximally contribute end-to-end from assay conception through data analysis and presentation of results to stakeholders. The individual will interact and work closely with colleagues across multiple functions within Preclinical Sciences, Medicinal Chemistry, Data and Computational Sciences, Data Technology and Engineering, and Research with the shared goal of advancing the Vertex portfolio. 

Key Duties and Responsibilities:    

• Leverage laboratory automation and data analytics technologies to design, execute, analyze, and interpret medium- to high-throughput laboratory experiments that evaluate toxicological endpoints. 
• Work jointly with scientific colleagues to identify and define data processing and analysis challenges, then plan and implement solutions including process improvements and bespoke computational workflows for data management, summarization, and visualization of internally- and externally-generated data. 
• Work with internal and external partners to guide the development, deployment, and continuous improvement of current and new quantitative approaches that improve the prediction and translation of drug safety risks. 
• Interact with strategic partners to design and execute laboratory studies and computational analyses to meet specific project needs. 
• Serve as a data interpreter, liaison, and communicator of key laboratory findings to stakeholders derived from a variety of screening assays executed in the group. 
• Communicate unambiguous critical and significant data to various bodies including project teams and Vertex leadership as required. 
• Continuously evaluate the landscape of emerging cellular models, screening assays, and data analytics opportunities in the space of toxicology that will help enrich and expand in-house capabilities. 
• Opportunities to supervise and mentor junior scientists. 
• Nurture external collaborations within academic and industrial sectors to enhance Vertex’s discovery toxicology capabilities. 

Knowledge and Skills:  

• Designing, executing, and interpreting biochemical and cell-based screening experiments. 
• Experience culturing and assaying cell lines, iPSC-derived, and/or primary cell types.  
• Developing computational workflows using R, Python, MATLAB, or similar scripting languages.   
• Cellular and molecular biology techniques, with an emphasis on multi-well plate-based formats. 
• Strong quantitative, analytical, and critical thinking skills. 
• Excellent writing, verbal communication, and presentation skills. 
• Strong scientific curiosity and desire to work in the discovery toxicology / drug safety space. 
• Strong desire and aptitude to serve as both a wet-laboratory and computational scientist. 
• Motivated and adaptable self-starter, with a strong desire to impact project progression. 
• Demonstrated track record of collaboration and teamwork. 
• Strong time management skills and comfortable working in a fast-paced environment. 

Education and Experience: 

• Bachelor's, Master’s, or PhD degree  
• PhD and 2+ years of academic or pharmaceutical industry experience or,  
• Master’s degree and 5+ years of academic or pharmaceutical industry experience or,  
• Bachelor’s degree and 8+ years of pharmaceutical industry experience 

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