Skills and qualifications:
1. Familiarity with physics-based modeling principles and best practices of the optimization oriented thermo-fluid systems modeling, such as HVAC systems and vapor compression cycles.
2. Familiarity with the optimal control theory and experience from the implementation of the optimal/advanced control of the HVAC systems, e.g., commercial building chiller plants, datacenter cooling system and district energy hub by using RTO, MPC, reinforcement learning, etc.
3. Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs, MIP, MILP), including attention to reliable convergence of such problems by using common solvers, e.g., IPOPT, CONOPT, CPLEX, Gurobi.
4. Familiarity and experience with development of computational platforms and tools in Python or equivalent.
5. Familiarity with using HPC and cloud-based platforms for computation at scale.
6. Demonstrated ability to work as part of a multidisciplinary team and an entrepreneurial attitude towards technological innovation in a global environment.
7. Self-starter who is well-organized in an international team environment, with proven communication skills.
Responsibilities
8. Deployment. Support that methods and tools developed in the group impact the Carrier business through engagement in global product projects, including capture and formulation of computational problems arising in such projects.
9. Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for large-scale numerical optimization are based on sound mathematical foundations and are deployed to match the needs of the Carrier business, including contributing to the architecture, development, testing and documentation of the methods and tools developed in the group.
10. Modeling for optimization. Support development of mathematical models for thermo-fluid systems are built based on principles and best practices that secure reliable application of numerical optimization algorithms.
11. Talent. Support development and training of staff within Carrier product teams and within the Computational Engineering group; contribute to talent pipeline by supervising student internships and theses.


Requirements
Education:
MEng or PhD in a relevant Engineering discipline (e.g., applied mathematics, thermal engineering, or chemical engineering) with 5+ years of experience.