Postdoctoral Fellow in Inverse Problems; Mathematics and Statistics
University of North Carolina at Charlotte
Position Number POST40
Working Title Postdoctoral Fellow in Inverse Problems; Mathematics and Statistics Division Academic Affairs Department Col Liberal Arts & Science (Col) Work Unit Mathematics and Statistics Work Location Fretwell Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary – Part-time Hours per week 40 Work Schedule Pay Rate 48,000 Minimum Experience/Education
The Postdoctoral appointee must have recently (within the last eight years) been awarded a Ph.D. or equivalent doctorate (e.g., Sc.D., M.D.)
Departmental Preferred Experience, Skills, Training/Education: Duties and Responsibilities
A Postdoctoral Fellow (“”postdoc””) is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop further the research skills acquired in their doctoral programs or to learn new research techniques, in preparation for an academic or research career. In the process of further developing their own research skills, it is expected that Postdoctoral Fellows will also play a significant role in the performance of research at the University and augment the role of graduate faculty in providing research instruction to graduate students. A Postdoctoral Fellow works under the supervision of a regular faculty member, who serves as a mentor to the Fellow, and it is expected that the faculty mentor will impart the realities, and variety, of scientific careers, and will encourage experiences outside the laboratory to broaden postdocs’ aspirations. Within the confines of the particular research focus assigned by that faculty member, the Postdoctoral Fellow functions with a considerable degree of independence and has the freedom (and is expected) to publish the results of his or her research or scholarship during the period of appointment. Thus, the role of Postdoctoral Fellows is clearly differentiated from full-time technical employees.
Postdoc appointments are characterized by all of the following conditions:
the appointee was recently (within the last eight years) awarded a Ph.D. or equivalent doctorate (e.g., Sc.D., M.D.); the appointment is temporary; the appointment involves substantially full-time research or scholarship; the appointment is viewed as preparatory for a full-time academic and/or research career; the appointee works under the supervision of a faculty member; and the appointee has the freedom and is expected to publish the results of his or her research or scholarship during the period of appointment.
As an EOE/AA employer and an ADVANCE Institution that strives to create an academic climate in which the dignity of all individuals is respected and maintained, the University of North Carolina at Charlotte encourages applications from all underrepresented groups. Applicants subject to criminal background check.
Other Work/Responsibilities Necessary Licenses or Certifications Proposed Hire Date 07/01/2023 Expected Length of Assignment 12 months Posting Open Date 02/03/2023 Posting Close Date 02/01/2024 Special Notes to Applicants
Please upload the following documents with your electronic submission: 1) Cover letter 2) Curriculum vita 3) Research interest statement 4) One to three papers/preprints reflecting your research experience Postdoctoral fellow in artificial intelligence approaches for inverse problems with applications to imaging. Applications are invited for a postdoctoral research position at the University of North Carolina at Charlotte. The duration of this position is a one year position with a possibility of renewal up to two additional years, subject to a budget approval. The successful candidate will work under the supervision of Professor Taufiquar Khan. The research of this candidate will be focused on implementation of AI and Deep Learning based algorithms, and providing performance guarantees for such algorithms for solving forward and inverse problems appearing in mathematical imaging. The candidate is also expected to have sufficient background on regularization of ill-posed inverse problems arising from coefficient inverse problems involving partial differential equations.