Computational Engineer Intern- Fall

About Carrier​
Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating solutions that matter for people and our planet for generations to come. From the beginning, we've led in inventing new technologies and entirely new industries. Today, we continue to lead because we have a world-class, diverse workforce that puts the customer at the center of everything we do. For more information, visit corporate.carrier.com or follow Carrier on social media at @Carrier
 

About this role
 

This internship will focus on reducing global energy consumption and carbon footprint in large-scale and highly integrated energy systems, including data centers, energy stations, and district heating/cooling networks.

Buildings account for 40% of energy consumption globally, and heating, cooling, and ventilation (HVAC) accounts for a significant share. These challenges can be addressed by using models, optimization, and ML methods. There are major computational challenges to fully realize the high-efficiency potential of integrated energy systems, including selection of system topology and equipment selection, quantification of energy efficiency, sensitivity to varying weather and load conditions, and operation, i.e., controls. Applications ranging from systems and control design, Model and data-driven discrete optimization, non-linear programming, and ML algorithm application are key to bringing forward innovative solutions.
 

Key Responsibilities

• Research, develop, and design computational algorithms to design and operate highly integrated energy systems to achieve optimal energy efficiency. 
• Develop automated computational workflows based on open-source packages in Python, R, Julia, etc.
• Deploy workflows to Carrier design teams. 
   

Required Qualifications

• Pursuing a Master’s degree in Applied mathematics, Chemical Engineering, Mechanical Engineering or Computational Engineering.
• Must have an overall GPA of 3.0 or higher.
• Must be eligible to work in the US without sponsorship.

Preferred Qualifications

• Pursuing PhD degree in Applied Mathematics, Chemical Engineering, Computational Engineering, or related fields.
• Theoretical foundations and practical experience with optimization algorithms, including discrete optimization and non-linear programming.
• Familiarity with thermodynamics and HVAC systems
• Coding skills in Python and Jupyter.

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