Modelling & Simulation Scientist, Computational Physics

Location: East Hanover

** Job Description*
* ** Are You Ready to Make It Happen at Mondelēz International?*
* ** Join our Mission to Lead the Future of Snacking. Make It With Pride.*
* Working as part of a cross-functional team covering broad modelling disciplines, you are an internally recognized expert in computational physics, a technical area of critical importance to the R&D function. You identify, define and solve complex modelling and simulation problems, tackling R&D's highest priority ingredient, product, process, and packaging challenges. Applying your in-depth knowledge of this technical specialty, you will drive rapid, high-quality innovation capabilities across Mondelez's portfolio, spanning chocolate, biscuit, gum, and candy categories.

** How you will contribute*
* You will bring computational physics modelling & simulation capabilities to Mondelez R&D's highest priority areas, developing solutions to move R&D work away from large, factory-scale trials towards small-scale or in silico predictions. Specifically, you will:

+ Design and deliver rapid simulation capabilities to drive solutions to business challenges.

+ Plan, lead, and manage modelling and simulation projects, scoping and proposing opportunities for sustained business impact.

+ Work closely with engineers and scientists to define complex technical challenges and agree on problem scope.

+ Communicate complex problems simply to non-technical audiences with relevant business context.

+ Define the datarequiredto build models; collaborate with internal teams or externalorganizationsto collect this information, which may include designing experimental tests.

+ Use software tools to design, build, test, and implement simulations - or select and manage delivery through an external partner.

+ Ensure simulations arevalidatedagainst experimental data, including any required experiments or factory trials.

+ Deploy models via simple UIs using the Mondelez-approved technology stack, in collaboration with IT and/or external partners.

+ Establish strategy and roadmap for integrating computational physics into R&D business processes.

+ Quantify and communicate the value of computational physics to stakeholders, the associated plan, and embed learnings into business processes to accelerate innovation and optimization.

+ Author best-practice documentation and knowledge-basearticles from project learnings.

+ Share knowledge and coach junior colleagues, building internal modelling & simulation capability across R&D.

+ Maintain data management practices - ensuring models, datasets, and simulation outputs are documented and stored in line with company data governance policies.

+ Research and keep pace with developments in relevant modelling, simulation, and virtual prototyping techniques.

+ Provide regular project updates to senior stakeholders, flagging potentialimpedimentsand resource needs.

** What you will bring*
* ** Physics & Modelling Fundamentals*
* + Fundamental understanding of materials' physical properties: how these are measured and modelled (e.g.viscosity, thermal conductivity, rheology).

+ Solid understanding of how physical transformations can be modelled(e.g.conduction of heat, fluid mixing, phase change).

+ Ability to decompose complex engineering problems into tractable steps and manage technical ambiguity.

+ Ability to create andvalidatemodels to test and predict real-world scenarios.

** Programming & Software*
* + Proficient in Python for scientific computing, data analysis, and model deployment (e.g.Num Py, Sci Py, pandas, matplotlib).

+ Familiarity withadditionallanguages such as MATLAB, C++, or Julia is advantageous.

+

Experience with machine learning and surrogate modelling frameworks (e.g.scikit-learn, Tensor Flow, orPyTorch).

+ Version controlproficiencyusing Git / Git Hub / Git Lab for collaborative code management.

** Simulation & Engineering Tools*
* Experience in one or more of the following:

+ Game-engine physics:
Unreal Engine, PhysX, Unity

+ Computational fluid dynamics: ANSYS Fluent, COMSOL Multiphysics

+ Finite element analysis (ANSYS, Abaqus)

+ Process modelling:gPROMS, Witness, Aspen

+ Discrete element method:
Rocky DEM, EDEM

+ Extended realities (AR/VR)…