2 positions at the Postdoctoral level are available in the Earth Research Institute and Department of Geography at the University of California, Santa Barbara.
The successful candidates will participate in the University of California Lab Fees project led by Professor Charles Jones “Mitigating and Managing Extreme Wildfire Risk in California” (http://clivac.eri.ucsb.edu). The project seeks to: 1) Understand the nature of changes in extreme fire-weather behavior in recent years, 2) Determine factors interacting with electric power system infrastructure and wildfire risk in California, 3) Examine reliability of energy supply and wildfire risk, and 4) Study fire-risk associated with vegetation management and electric power grid infrastructure.
Position #1 - The selected candidate will be primarily involved in analyzing simulations from the Coupled Model Inter-comparison Project (CMIP6) and multi-year regional model simulations degenerated in this project to identify and understand recent changes in extreme wildfire regimes in California. Experience with the Weather Research and Forecasting (WRF) model is highly desirable.
Position #2 - The candidate will be primarily involved in performing multi-year simulations with the Weather Research and Forecasting (WRF) model and uncoupled fire spread models. Experience in wildfire research is highly desirable.
The two positions are full-time research training under the mentorship of Dr. Charles Jones. Both positions are full time and offer competitive salary and benefits. The initial appointment for each position is one year and continuation for another two years will be based on performance and availability of funding. The ideal starting date for the position is March 1, 2020.
Basic qualifications: Ph.D. in atmospheric sciences, or a closely related field, by March 1, 2020.
Additional qualifications: 3 years experience in analyzing large data sets of global and regional model simulations. Appointees should have a minimum 2 years experience working independently and collaboratively within a multidisciplinary team.
Preferred qualifications: Demonstrated experience in statistical analyses, Weather Research and Forecasting, Linux environment and programming skills. Strong written and oral communication skills demonstrated in peer review publications and presentations in professional conferences. Experience with IDL, Python, NCL, Matlab and/or FORTRAN.
Please log in to https://recruit.ap.ucsb.edu/apply/JPF01717 to submit your cover letter with qualifying research experience, a current CV, representative publications, and arrange for 3 letters of recommendation. For more information, please send email attention JPF01717 to payroll@eri.ucsb.edu. For primary consideration, apply by 01/31/2020.
UCSB is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.
The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The successful candidates will participate in the University of California Lab Fees project led by Professor Charles Jones “Mitigating and Managing Extreme Wildfire Risk in California” (http://clivac.eri.ucsb.edu). The project seeks to: 1) Understand the nature of changes in extreme fire-weather behavior in recent years, 2) Determine factors interacting with electric power system infrastructure and wildfire risk in California, 3) Examine reliability of energy supply and wildfire risk, and 4) Study fire-risk associated with vegetation management and electric power grid infrastructure.
Position #1 - The selected candidate will be primarily involved in analyzing simulations from the Coupled Model Inter-comparison Project (CMIP6) and multi-year regional model simulations degenerated in this project to identify and understand recent changes in extreme wildfire regimes in California. Experience with the Weather Research and Forecasting (WRF) model is highly desirable.
Position #2 - The candidate will be primarily involved in performing multi-year simulations with the Weather Research and Forecasting (WRF) model and uncoupled fire spread models. Experience in wildfire research is highly desirable.
The two positions are full-time research training under the mentorship of Dr. Charles Jones. Both positions are full time and offer competitive salary and benefits. The initial appointment for each position is one year and continuation for another two years will be based on performance and availability of funding. The ideal starting date for the position is March 1, 2020.
Basic qualifications: Ph.D. in atmospheric sciences, or a closely related field, by March 1, 2020.
Additional qualifications: 3 years experience in analyzing large data sets of global and regional model simulations. Appointees should have a minimum 2 years experience working independently and collaboratively within a multidisciplinary team.
Preferred qualifications: Demonstrated experience in statistical analyses, Weather Research and Forecasting, Linux environment and programming skills. Strong written and oral communication skills demonstrated in peer review publications and presentations in professional conferences. Experience with IDL, Python, NCL, Matlab and/or FORTRAN.
Please log in to https://recruit.ap.ucsb.edu/apply/JPF01717 to submit your cover letter with qualifying research experience, a current CV, representative publications, and arrange for 3 letters of recommendation. For more information, please send email attention JPF01717 to payroll@eri.ucsb.edu. For primary consideration, apply by 01/31/2020.
UCSB is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.
The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.