Project Scientist (Building Technologies and Urban Systems)

📁
Research/Science
💼
BU-Bldg Technology Urban Systems
📅
88618 Requisition #

Berkeley Lab’s Building Technology and Urban Systems (BTUS) Division has an opening for Project Scientist!


In this role, you will collaborate on applied research and demonstration efforts using machine learning techniques to predict building performance, optimize building energy use, and occupant comfort for office buildings.  You will participate in the formulation of ideas needed for grant writing, assisting in the grant writing process, and assisting with technical leadership of on-going research activities.


The position requires a strong background in building energy efficiency, the use of machine learning techniques and tools, and a track record in performing research.


What You Will Do:

  • Support the development and application of machine learning techniques for two projects.

  • Use GAN (generative adversarial network) technique to cluster electric load shapes for residential and commercial buildings.

  • Use deep learning algorithms to estimate and predict occupancy, plug-loads and internal heat gains in commercial buildings that feed into model predictive controls.

  • Use deep reinforcement learning algorithms to optimize control strategies for minimizing energy cost while enhancing occupant wellbeing and building-grid integration.

  • Contribute to the development of research proposals on using machine learning to improve building performance.

  • Publish research results in journals, present findings at national conferences and support industry on adopting the research outcomes and tools

  • Conduct research and development of new methods to model occupant behavior.

  • Develop methods to model and simulate occupant behavior at the community or city scale.

  • Develop models and tools to predict occupant-driven loads capturing their diversity and stochastics.


What is Required:

  • Advanced degree (or equivalent training) in Architecture, Engineering or a related area relevant to Building Science and Technology.

  • In-depth knowledge and experience with architectural and/or mechanical systems in buildings.

  • Hands-on experience using machine learning techniques for data analytics.

  • Broad knowledge about energy efficiency in buildings.

  • In-depth knowledge about occupant comfort and behavior.

  • Excellent oral communication and presentation skills with experience presenting at meetings, workshops, and conferences.

  • Strong interpersonal communication skills with the ability to communicate effectively with funders and stakeholders.

  • Excellent written communication skills with a strong record of journal publication.

  • Ability to generate new ideas for research proposal development.

  • Capability of working on multiple tasks and projects.


What We Desire:

  • Ph.D. with two or more years of research experience in Architectural Engineering or Building Science and Technologies.

  • Experience in using artificial intelligence and machine learning techniques and tools to solve building energy problems.

  • Demonstrated expertise in interdisciplinary nature of human comfort and behavior through project activities or Journal/conference publications.

  • Strong knowledge of building science, machine learning, and human behavior.

  • Strong knowledge of programming languages, e.g., Python, Modelica.

  • Hands on experience using machine learning toolkit.

  • Self-motivation to learn new knowledge to meet emerging research needs.


The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on October 31, 2019.   


Notes:

  • This is a full time, M-F, exempt from overtime pay (monthly paid), 1 year, Term appointment with the possibility of extension for up to a maximum of 5 years based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.

  • Salary is commensurate with experience.

  • 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.

  • Work will be primarily performed 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.


Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities.  To view information about the many rewards that are offered at Berkeley Lab- Click Here.


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. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.  Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."


Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.

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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. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."

 

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The Lawrence Berkeley National Laboratory provides accommodation to otherwise qualified internal and external applicants who are disabled or become disabled and need assistance with the application process. Internal and external applicants that need such assistance may contact the Lawrence Berkeley National Laboratory to request accommodation by telephone at 510-486-7635, by email to eeoaa@lbl.gov or by U.S. mail at EEO/AA Office, One Cyclotron Road, MS90R-2121, Berkeley, CA 94720. These methods of contact have been put in place ONLY to be used by those internal and external applicants requesting accommodation.