Berkeley Lab's Building Technology and Urban Systems (BTUS) Division is looking for a Postdoctoral Fellow to join their Modeling & Simulation Group!

In this role, you will develop, implement, and evaluate model predictive control (MPC) tools (Modelica-, FMI- and python-based) for building HVAC and district energy systems. We are looking for a talented researcher familiar with HVAC systems and theories in optimization, control, and machine learning in addition to the use of available software. You will be expected to work under the guidance of scientists and collaborate effectively with multi-disciplinary research and development teams including researchers within and outside LBNL.

What You Will Do:

• Conduct research, develop, and deploy new generation modeling tools for building design and operation based on the Modelica and FMI standards.
• Investigate cutting-edge algorithms and tools in the fields of system identification, machine learning, optimization, and model predictive control.
• Test, identify or develop MPC and optimization algorithms for building HVAC systems especially heat pumps.
• Develop MPC tool(s) for grid-interactive-efficient buildings using the Modelica, FMI standards, and python.
• Evaluate the MPC tool(s) using Modelica- and FMI-based simulation platforms.
• Deploy, implement, and evaluate MPC tools at laboratory environments and field sites.
• Publish research results in journals, present findings at national and international conferences, and work with industry on testing and deploying the research.
• Contribute to securing funding for the development of new control technologies for buildings.

What is Required:

• A recent Ph.D. Degree in Chemical Engineering, Electrical Engineering, Computer Science, Mechanical Engineering, Architectural Engineering or related field.
• Solid background in dynamic systems, control, optimization, and thermo-fluid systems (with application to energy systems in buildings).
• Strong knowledge of programming languages, Modelica and Python in particular, and version control (git).
• Experience in the use of optimization software (such as CasADi, Gurobi, and Pyomo).
• Demonstrated strong experience in optimization and/or controls through journal and conference publications.
• Excellent verbal and written communication skills including the ability to clearly communicate goals, parameters, objectives, and outcomes of the research.
• Strong analytical and interpersonal skills including the ability to work independently as part of a team on multiple tasks and projects.

What We Prefer:

• Solid background in the computational graph, automatic differentiation, and symbolic manipulation.
• Experience with machine learning and data analysis tools such as TensorFlow.
• Strong interest in combining modern computing technologies for modeling and simulation of HVAC and control systems, integrating these technologies in large software packages, and working with teams that deploy them to the buildings industry.

For full consideration, please apply by March 7, 2021, with the following application materials:

• Cover Letter - Describe your interest in this position and the relevance of your background.
• Curriculum Vitae (CV) or Resume.

Notes:

• This is a full-time, M-F, exempt from overtime pay (monthly paid), 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience.
• Salaries for postdoctoral positions depend on years of experience post-degree and are predetermined based on postdoctoral step rates.
• This position is represented by a union for collective bargaining purposes.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• This position is funded by the California Energy Commission, with a requirement of in-state residency. Due to COVID-19, this position will initially be performed remotely but limited to individuals who can reside in the State of California. Once Bay Area shelter-in-place restrictions are lifted, work may resume onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

Learn About Us:

Berkeley Lab (LBNL) addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy's Office of Science.

The Building Technology and Urban Systems (BTUS) Division advances energy efficiency and demand response in the built environment--one of the world's most critical energy and environmental challenges. Through research, partnership programs, and software tools, we promote energy and cost savings while improving comfort, health, and safety.

Berkeley Lab's Postdoc Program is committed to providing Postdoctoral Researchers and Visiting scholars with a positive and impactful experience to jump-start their career through premium research and career development, networking opportunities, mentoring programs, and strong community. For more information, please visit our Berkeley Lab Postdoc Resources site and our Berkeley Lab Postdoc Association site.

Berkeley Lab is committed to Inclusion, Diversity, Equity, and Accountability (IDEA) and strives to hire individuals who share these same values and commitments.

Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."