Research Scientist - Modelling

As a Research Engineer in Modeling at BASF Environmental Catalyst and Metal Solutions (ECMS), you will play a crucial role in driving innovation in automotive aftertreatment systems by applying your expertise in reaction engineering, kinetics, transport, and data analytics. You will be a key member of the Research, Development & Application (RD&A) department, supporting cross-functional teams across catalyst design, testing, and application. Your Key Responsibilities will include: - Analyzing and processing data from automotive aftertreatment systems testing to gain insights into performance and reaction mechanisms. - Developing and refining kinetic models that consider reaction kinetics, mass transfer, and heat transfer fundamentals to guide catalyst screening, system design, and optimization. - Collaborating closely with cross-functional teams, such as testing, catalyst design, and application, to utilize models for experiment design, validation, and performance optimization. - Effectively communicating technical findings and insights to stakeholders across the organization. - Developing and applying machine learning models to enhance physics-based simulations and accelerate model-driven innovation. Qualifications required for this role: - Ph.D. in Chemical Engineering or a related discipline, with a thesis or research focus on catalysis, reaction kinetics, or chemical reaction engineering. Research experience in automotive emissions control chemistry or related catalysis applications is desirable. - Demonstrated experience in developing and applying kinetic models for catalytic reaction systems, encompassing steady-state and transient conditions, and integrating reaction kinetics, mass, and heat transfer fundamentals. - Proficiency in computational modeling and data analysis, including the use of Python or similar programming languages. - Experience with machine learning model development and data-driven methods to complement physics-based modeling is a plus. - Strong collaboration skills, with the ability to work effectively in cross-functional, multidisciplinary R&D teams. - Excellent written and verbal communication skills to convey complex technical concepts clearly to diverse audiences.,