About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace Defense, Biomedical Life Sciences, Intelligence Sensing, and Energy Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida.

CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years.

com CFD Research is seeking a highly skilled Computational Mathematician/Physicist to join our Biotechnology and Life Sciences team, where they will play a central role in formulating and developing advanced mathematical models and computational methods to solve complex, real-world problems. The successful candidate will combine expertise in mathematical modeling and numerical methods with the practical coding skills needed to implement, test, and refine these models in scientific computing environments. The candidate will also support data-driven research efforts across domains such as biology, engineering, and physical sciences.

This role offers the opportunity to work at the intersection of theory and application in a collaborative, fast-paced environment focused on innovation and technical excellence.

Key Responsibilities

Formulate and derive new mathematical models to simulate complex systems and processes Implement, analyze, and validate models using appropriate numerical methods and algorithms for solving differential equations, optimization problems, and stochastic systems Translate real-world problems into computational frameworks and scalable solutions Collaborate with experimental scientists and engineers to integrate modeling with empirical data Develop high-performance computing (HPC) solutions and optimize code for efficiency and scalability Document methodologies, code, and results Maintain best practices in version control, reproducibility, and software development Contribute to scientific reports, proposals, and peer-reviewed publications

Qualifications

Required PhD with 3+ years of relevant experience (or equivalent) in Applied Mathematics, Computational Science, Physics, Engineering, or a closely related field Demonstrated experience developing original mathematical/computational models and simulations for complex systems Strong foundation in numerical analysis, linear algebra, differential equations, and/or stochastic modeling Familiarity with data analysis and visualization tools Working proficiency in scientific programming (e.g., Python, MATLAB, Julia, C/C++), with the ability to build clean, maintainable implementations of your own models Demonstrated intellectual curiosity and a willingness to learn and apply new methods, tools, and scientific domains as project needs evolve Strong analytical, critical thinking, and problem-solving skills with attention to detail Excellent written and verbal scientific communication skills, with the ability to convey complex mathematical concepts and collaborate effectively in multidisciplinary teams Proven ability to work independently, manage multiple projects, and troubleshoot complex technical challenges Preferred Experience developing computational models of preclinical biological systems (e.g., in vitro assays, cell-based systems, or other fit-for-purpose preclinical models) Background in a domain area such as bioinformatics, infectious disease modeling, flui