Demonstrates expertise in developing and applying hybrid models for simulation and process optimization, utilizing physics-informed AI methods and strong domain knowledge of industrial plant dynamics. Proficient in collaborating across diverse teams and presenting complex concepts to various audiences.

Highest-signal resume keywords

Model-Based SimulationPhysics-Informed AI MethodsMachine Learning and AI MethodsSimulation and Modeling ToolsIndustrial Plant Dynamics

Tech Stack

Tools & technologies

PythonC++

About the role

Key responsibilities & impact

Bridge academic research and industrial applications in simulation, system modeling, and industrial digitalization
Develop and apply hybrid models combining analytical and data-driven methods for process-industry and manufacturing assets
Apply physics-informed AI methods to develop interpretable, efficient, and reliable models for simulation and process optimization
Integrate components, control logic, and physical dynamics at plant or system level
Build simulation models to validate control logic, support scenario analysis, enable process optimization, and support operator training
Translate industrial plant-dynamics knowledge into robust simulation and monitoring systems
Initiate, guide, and contribute to applied research projects
Provide consultancy to product development teams
Collaborate with ABB divisions, customers, partners, startups, and academic institutes internationally
Build prototypes and demonstrators and develop maintainable simulation tools
Present work to expert and management audiences, scientific conferences and journals, and trade fairs
Secure intellectual property through patent applications

Requirements

What you’ll need

Degree in engineering, scientific computing, mathematics, physics, or a related discipline with specialization in modeling and simulation
Academic experience (PhD) or professional experience in applied modeling and simulation
Experience with model-based, data-based, and/or physics-informed AI-based simulation and monitoring methods for dynamic systems
Domain knowledge of industrial plant or process dynamics, focused on system-level behavior and system integration
Experience with machine learning and AI methods, including neural networks, deep learning, or reinforcement learning, preferably applied to dynamical systems, process modeling, or real-world applications
Experience in automation engineering, industrial control, condition monitoring, advanced process control, or optimization is beneficial
Hands-on software development and software architecture experience is a plus, such as Python, C++, or Modelica
Hands-on experience with simulation and modeling tools is a plus, such as OpenModelica, Julia, FMU-based co-simulation, DWSIM, IDEAS PSE, Dymola, Aspen HYSYS, MATLAB Simulink, or Simscape
Excellent written and verbal communication skills in English
German is a plus
Cross-cultural communication skills, creativity, initiative, enthusiasm, and result-orientation

Benefits

Comp & perks

Employee Share Acquisition Plan
Retirement Plan
Canteen
Flexible Work Practices

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Modeling and SimulationData-Driven MethodsProcess OptimizationAutomation EngineeringSoftware DevelopmentSoftware ArchitectureNeural NetworksDeep LearningReinforcement LearningControl Logic Integration

Soft Skills

Excellent Communication SkillsCross-Cultural CommunicationCreativityInitiativeResult-Orientation

Tools & Technologies

PythonC++ModelicaOpenModelicaDWSIMIDEAS PSEDymolaAspen HYSYSMATLAB SimulinkSimscape

Industry Keywords

Industrial DigitalizationProcess IndustrySystem IntegrationCondition MonitoringAdvanced Process Control