Postdoctoral Scholar in Applied Mathematics
Position overview
Position title: Postdoctoral ScholarApplication Window
Open date: March 21, 2024
Next review date: Tuesday, Apr 30, 2024 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Sunday, Jun 30, 2024 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Position description
Prof. Harish S. Bhat [http://faculty.ucmerced.edu/hbhat/] in Applied Mathematics at UC Merced is seeking applicants for a postdoctoral position in applied/computational mathematics.
The postdoctoral scholar will develop new computational methods that fuse modern machine learning methods with first-principle, time-dependent, nonlinear/nonlocal partial differential equations.
Through this fusion, the postdoctoral scholar will develop methods that learn unknown/missing terms in models of time-dependent physical systems, with the aim of
(i) improving the model's accuracy,
(ii) reducing the model's dimensionality, and
(iii) controlling the system's behavior.
The postdoctoral scholar will work closely with Prof. Bhat and will also be co-mentored by Prof. Christine Isborn (Chemistry, UC Merced).
The postdoctoral scholar will be expected to lead and/or to participate in research projects; this will include pen-and-paper mathematics, development of code, and design/execution of numerical experiments leading to scientific discovery. The postdoctoral scholar will be expected to coauthor manuscripts for publication in peer-reviewed journals and proceedings, to develop and publish open-source software, to present research findings at conferences/seminars, and to work with graduate and undergraduate student researchers.
Qualifications
PhD in Applied Mathematics or related field
Experience developing new computational methods, especially for Hamiltonian/Lagrangian systems (whether classical or quantum) and implementing these methods in code on large-scale computational clusters
Strong verbal and written communication skills
Experience publishing peer-reviewed articles and presenting at conferences/seminars
Preferred qualifications include expertise in at least one of the following areas:
(1) machine learning for time-dependent physical systems
(2) numerical optimal control
(3) constrained nonlinear optimization
(4) nonlinear system identification
(5) numerical solution of the time-dependent Schrodinger equation and/or related evolution equations that arise in molecular quantum mechanics
Within areas (1) through (4), an emphasis on Hamiltonian/Lagrangian systems, whether classical or quantum, is preferred.
Experience with machine learning frameworks such as JAX, PyTorch, and/or TensorFlow is preferred.
Application Requirements
Curriculum Vitae - Your most recently updated C.V.
Cover Letter
- 3 required (contact information only)
Help contact: snspersonnel@ucmerced.edu
About UC Merced
The University of California, Merced, is the newest of the University of California system’s 10 campuses. With over 9,000 undergraduate and graduate students (https://cie.ucmerced.edu/analytics-hub/student-statistics), UC Merced is committed to interdisciplinary excellence in research and teaching as well as to diversity, equity and inclusion. Ranked as one of the best public universities in the nation by U.S. News and World Report, UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).
The University of California, Merced is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. This includes the University of California Policy on Vaccination Programs: https://policy.ucop.edu/doc/5000695/VaccinationProgramsPolicy.