PRODUCT AND PROCESS SYSTEMS MODELING MISSION
THE PRODUCT AND PROCESS SYSTEMS MODELING SECTION INTEGRATES DATA AND THEORY TO DEVELOP INNOVATIVE PRODUCTS AND PROCESSES. WE ARE RESPONSIBLE FOR THE RESEARCH, DEVELOPMENT, AND DEPLOYMENT OF NEW MODELING CAPABILITIES WHICH ARE REQUIRED TO DRIVE INNOVATION AND PRODUCTIVITY IN PRODUCT AND PROCESS DEVELOPMENT. WE ARE PART OF P&G’S CORPORATE FUNCTIONS. WE APPLY THE PROCESS SYSTEMS ENGINEERING PARADIGM IN ALL OUR BUSINESS UNITS TO THE DESIGN AND OPTIMIZATION OF COMPLEX PRODUCTS AND PROCESSES.
THE PRODUCT AND PROCESS SYSTEMS MODELING SECTION IS RECRUITING A POST-DOCTORAL RESEARCH ASSOCIATE TO SUPPORT THE USE OF PRODUCT AND PROCESS SYSTEMS MODELLING WITHIN P&G. THE SUCCESSFUL CANDIDATE WILL USE EQUATION-ORIENTED MODELLING TOOLS SUCH AS GPROMS TO DEVELOP, VALIDATE, AND EXPLOIT MODELS TO MAKE OPTIMAL BUSINESS DECISIONS.
At a minimum:
- The candidate will possess a Ph.D. in Chemical Engineering with a specialization in process systems engineering.
- The candidate must have demonstrated, in previous work, the ability to
- use chemical engineering science to derive the appropriate continuum equations for a given system (unit operation, product or other application);
- implement these equations in a suitable modelling package or programming environment;
- verify the implementation of the model;
- validate the model using experimental data; and
- communicate the results to an audience in written and verbal form.
- The candidate must have a sound understanding of the numerical methods that were used to solve the model.
- The candidate must have and be able to demonstrate knowledge and experience of developing and using models with gPROMS.
- The candidate must demonstrate the ability to communicate clearly using English.
The ideal candidate will demonstrate the ability to:
- Translate a problem description into a plan of action.
- Communicate plans, concepts, and results to audiences of varying technical capabilities.
- Work effectively in a multi-disciplinary and multi-cultural environment.
- Stay up to date on the state-of-the art in systems modeling technologies.
Knowledge of one or more of the following topics is a plus
- Mathematical optimization techniques
- Model validation techniques including identifiability, estimability and sensitivity analyses
- Discretization techniques for partial differential equations
- Statistical thermodynamics