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Post-Doctoral Scholar - Applied Mathematics

Recruitment Period

Open December 8th, 2018 through January 31st, 2019

Description

The University of California, Merced, is the newest of the University of California system’s 10 campuses and the first American research university built in the 21st century. With more than 7,500 undergraduate and graduate students, UC Merced offers an environment that combines a commitment to diversity, inclusion, collaboration and professional development. With bachelor’s, master’s and doctoral degree programs, strong research and academic partnerships, and community involvement, the UC Merced campus is continually evolving and requires talented, knowledgeable and dynamic educators, researchers, management and staff.

Ranked among the best public universities in the nation by U.S. News and World Report, UC Merced is uniquely equipped to provide educational opportunities to highly qualified students from the San Joaquin Valley and throughout California.

The campus enjoys a special connection with nearby Yosemite National Park, is on the cutting edge of sustainability in construction and design, and supports the economic development of Merced and the region.

In Fall 2016, UC Merced broke ground on a $1.3 billion public-private partnership that is unprecedented in higher education. The Merced 2020 Project will nearly double the physical capacity of the campus by 2020, enhancing academic distinction, student success and research excellence. UC Merced has also built the Downtown Campus Center, a $33 million, three-story administrative building in the heart of Merced.

The postdoctoral researcher will work under an NSF-funded Collaborative Research (with UC Merced, UT Austin and MIT) entitled: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion (see https://hippylib.github.io ).

The postdoctoral researcher will perform research in the field of large-scale Bayesian inverse problems, and on the implementation of new features in hIPPYlib. The postdoc will contribute to the research dissemination and will also help build the user/developer community by attending and speaking at conferences, workshops and summer schools at local and international events.

Required qualifications include a PhD in applied mathematics, computational science, or a related field as well as advanced-level knowledge of the Python programming language. Research interest and experience in numerical analysis (e.g., finite element methods), numerical optimization, numerical linear algebra, inverse problems and/or uncertainty quantification is desired. Experience with C++ and github is a plus.

Interested applicants are required to submit 1) a cover letter 2) a curriculum vitae, 3) three letters of reference which should be electronically uploaded by the letter writers (instructions will be provided by the application system). Letters of reference should be received no later than 1/31/2019. 4) A research statement.

Review of applications will begin immediately and will continue until the position is filled with a final closing date of 1/31/2019.

Salary is based on the University of California Academic Salary Scales. This is a full-time, one-year appointment with the possibility of renewal based on availability of funding, ongoing operational needs and satisfactory performance.

The University of California, Merced is an affirmative action/equal opportunity employer with a strong institutional commitment to the achievement of diversity among its faculty, staff, and students. The University is supportive of dual career couples.

For more information, please contact Noemi Petra at npetra@ucmerced.edu.

Job location

Merced, CA

Requirements

Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter

  • Statement of Research

Reference requirements
  • 3 letters of reference required

How to apply

  1. Create an ApplicantID
  2. Provide required information and documents
  3. If any, provide required reference information
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