Postdoctoral Scholar - The Energy Institute - Haas School of Business
The Energy Institute at Haas at the University of California, Berkeley seeks applications for a Postdoctoral Scholar-Employee (Title Code 3252), with expertise in machine learning and power systems analysis, at 100% full-time with an expected start date of as soon as possible.
This position is full-time for a one-year term with the possibility of renewal, contingent on performance and availability of funding. (Salary will commensurate with experience).
The Postdoc would join an exciting new project on Mitigating and Managing Extreme Wildfire Risk in California with a cross-disciplinary team of researchers spanning three UC campuses and two National Labs. Funded by the 2020 UC Lab Fees Research Program, we have assembled a multidisciplinary team from UC Berkeley, UC Santa Barbara, UC San Diego, Lawrence Berkeley and Lawrence Livermore National Labs to investigate the interactions among four research themes climate change and fire-weather, vegetation management, the electric power grid and associated policies and their influences on wildfires. The UC Berkeley team will work in close collaboration with partners to investigate the following questions: What observable factors interact with power system infrastructure to increase wildfire risk in California? How do trade-offs between reliability of supply and wildfire risk vary across alternative de-energizing protocols? Can cost-effective investments be implemented in the near future to minimize fire-risks associated with vegetation management and power grid infrastructure?
The postdoctoral scholar will work on electrical infrastructure ignition prediction models and decision support tools for depowering decisions to develop power flow assessments of depowering rules. The scholar will be supervised by Duncan Callaway (Energy and Resources Group and Electrical Engineering and Computer Science) and will collaborate with research engineers at Lawrence Berkeley National Lab and other project personnel.
Basic qualification (at time of application):
- Ph.D. (or equivalent international degree), or enrolled in a Ph.D. (or equivalent international degree) granting program at the time of application.
- Ph.D. (or equivalent international degree) by start date.
- Ph.D. in Electrical Engineering, Civil Engineering, Mechanical Engineering, Computer Science or a related field.
- Research experience at the interface of power system decision making and machine learning models
- Data analysis experience with very large spatial data sets
- Ability to work with a mixture of infrastructure and environmental data sets
- Research experience constructing, implementing and interpreting machine learning models and nonlinear programming models - including mixed integer programs and convex optimization models.
Please visit the following link to apply: https://aprecruit.berkeley.edu/apply/JPF02619
questions to David Beausoleil at email@example.com
Letters of reference will only be solicited for finalists. References should be from individuals who are familiar with the applicant's written work and qualifications for the position. All letters will be treated as confidential per University of California policy. Please refer potential referees, including when letters are provided via a third party (i.e. a dossier service or career center), to the UC Berkeley statement of confidentiality (http://apo.berkeley.edu/evalltr.html
) prior to submitting their letters.
The Hass School of Business is interested in candidates who will contribute to diversity and equal opportunities in higher education through their teaching or research.
UC Berkeley Postdoctoral Scholars are academic appointees in an organized bargaining unit and are currently exclusively represented by United Auto Workers Local 5810.
The University of California 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. For the complete University of California nondiscrimination and affirmative action policy see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct