UES is seeking an experienced data scientist to support the Predictive Toxicology team at the US Air Force Research Laboratory at Wright Patterson Air Force Base, Dayton, OH. The successful candidate will be responsible for analyzing large data sets from environmental exposure/toxicology sampling studies from a variety of sources, such as physiological modeling of chemical toxicity and exposure. The incumbent will have substantive experience with a variety of downstream analyses, including modeling data trends, statistical analysis and building predictive algorithms/models. Additional duties will also include development of analytics and data visualization tools, as well as data management and automation protocols as needed. The successful candidate will be a self-starter, work well in a team-based environment, and able to think creatively towards implementing novel modeling approaches. Special consideration will be given to candidates with experience in “Big Data,” ‘omics analyses, QSAR, Ordinary differential equations, and machine learning.

Qualifications:

• A minimum of a Master's degree in Applied Mathematics, Statistics, Engineering, Computational Toxicology or highly related field is required; a PhD in these disciplines is preferred.
• A minimum of two years of relevant experience is required.
• Fluency in Python and R is required. Proficiency in MATLAB is preferred.
• Proficiency in technical writing and developing presentations is highly preferred.
• Demonstrated proficiency in Systems Biology modeling, such as PBPK and IVIVE is highly preferred
• US citizenship is required for this position

Additional Information

UES, Inc. is an innovative science and technology company providing customers with superior research and development expertise since its inception in 1973. Our long-term success is a direct result of a strong commitment to the success of our employees. We look forward to reviewing your application.

UES, Inc. is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. U.S. Citizenship is required for most positions.