Development of material in inverse problems and data assimilation
Opportunity Description:
We are looking for an undergraduate researcher who would be willing to implement several algorithms to produce pedagogical figures to include in a set of lecture notes and new chapters for an upcoming text. The goal is to improve the instructor’s lecture notes and chapters by including additional figures and new material.
Primary Responsibilities:
The undergraduate researcher will be expected to produce high-quality, pedagogical figures to illustrate the performance and implementation of several algorithms. In addition, the undergraduate researcher will help add new materials to the current set of lecture notes.
Minimum Qualifications and/or Eligibility Requirements:
The student should have a good background on mathematics and statistics, as well as the necessary coding skills to produce high-quality figures.
Familiarity with LaTeX or willingness to learn.
Ideal candidate will have had courses/training in probability (at least at the level of 24400).
Knowledge or skills gained from the experience:
Deep understanding of the topic of the lecture notes, and implementation of important algorithms. The undergraduate researcher will also improve their scientific writing and communication skills.
Application Process:
To apply for this opportunity, please submit in *one* pdf document, the following materials:
- Current CV with the names and contact details of two references at the end;
- 350-word statement of interest in the opportunity (not a cover letter);
- Unofficial transcript
- Name of two references
Your application file should be emailed directly to the research team at the College Center for Research and Fellowships: ccrf-research@uchicago.edu
Application Requirements:
Daniel Sanz-Alonso