Post Doctoral Fellow

Advertised Job Summary

This is a Postdoctoral Associate position in the area of mathematical foundations of data science and machine learning in a boarder sense in the Department of Mathematics. The candidates are expected to contribute to synergistically bridging important theoretical developments in mathematics and vibrant emerging mathematical foundations in Data Science/Machine Learning.

Job Duties

• Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research projects, ensuring the advancement of scientific knowledge. Additionally, they will actively participate in seminars, both as a learner and a presenter, to stay updated with the latest developments in their field and to share their findings. (25%)
• Mentorship will be a key responsibility, as the postdoc will guide graduate students through their research endeavors, providing valuable insights and support. Furthermore, they will mentor undergraduate students participating in the summer Research Experiences for Undergraduates (REU) program, helping to foster the next generation of researchers by offering guidance, feedback, and encouragement throughout their projects. (40%)
• Organizing the Research Experience for Undergraduates (REU) summer school, supervising graduate students and undergraduate students, leading group discussions and research project during the 6-week summer program. (10%)
• Attending bi-weekly team meetings and bi-weekly RTG seminars. (5%)
• Supervising graduate and undergraduate students’ research as needed. (10%)
• Attending relevant conferences to make representations and reports the outcomeof the research as needed. (5%)
• Any other related duties, as asked by PI or CoPIs. (5%)

Minimum Qualifications

• Requires a Doctoral (Ph.D.) degree in area of research specialty by the start date of employment.
• Programming and computing capabilities in at least one programming language is required.
• Prior knowledge in parallel/GPU computing.