Position title: Postdoctoral Scholar
Open April 19th, 2021 through Wednesday, May 19, 2021 at 11:59pm (Pacific Time)
The McKinnon group at the University of California, Los Angeles (UCLA) is seeking a postdoctoral scholar to develop and apply novel statistical and machine learning methods towards the goal of modeling and predicting temperature variability and extremes. We are particularly interested in quantifying the relative roles of the atmosphere and land surface in causing or modifying the statistics of daily temperature. The postdoctoral scholar will work closely with both Professor McKinnon and Dr. Isla Simpson at the National Center for Atmospheric Research (NCAR) to analyze large and diverse datasets, including station data, reanalyses, and climate model output. The selected applicant will also work in parallel with Wenwen Kong, a current postdoctoral scholar using idealized climate model simulations as a tool to explore these same science questions. The position is funded in part by the National Science Foundation.
While we prefer that the selected candidate will join us in-person at UCLA once travel and relocation is possible, we are open to discussing remote work. We will support conference travel, travel to collaborate in-person with Dr. Simpson in Boulder, and other professional development. The successful candidate would join an active community of postdocs at UCLA; see https://www.postdoc.ucla.edu/ for resources and information.
- Develop descriptive and predictive statistical models for temperature variability and extremes
- Integrate observationally-based analyses with physical insights from a hierarchy of climate models
- Publish results in high-quality, peer-reviewed journals
- Present results at conferences and seminars
The initial appointment will be for a 12 month period, with the possibility of renewal for an additional 12 months subject to satisfactory performance. Salary will be commensurate with experience.
The selected candidate can begin the position in the summer or fall.
PhD in atmospheric sciences or related field
Experience with statistical modeling and/or machine learning
Excellent written and oral communication skills
Proficiency in python (preferred), Matlab, or other data analysis software
Ability and desire to pursue research both independently and as part of a team
- Curriculum Vitae – Your most recently updated C.V.
- 3 required (contact information only)
Only references for shortlisted candidates will be contacted.
Apply link: https://recruit.apo.ucla.edu/JPF06365
Help contact: firstname.lastname@example.org
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: UC Nondiscrimination & Affirmative Action Policy.