Assistantship Opportunity with Prof. Vinodchandran Variyam
Prof. Vinodchandran Variyam is seeking an advanced undergraduate student or a graduate to join a research project. This position offers an exciting opportunity to contribute to NSF-funded research projects focused on the foundations of machine learning and big data algorithms, including the foundations of algorithmic reproducibility. It is particularly well-suited for students with a strong mathematical background who are interested in pursuing an academic career at world-class research institutions.
Area of Expertise Required:
- Mathematical Foundations: Strong understanding of mathematical principles, with a particular emphasis on probability theory and discrete mathematics.
- Algorithms: Solid knowledge of algorithms, including design, analysis, and implementation.
- Educational Background: Applicants should be completing either undergraduate or graduate degree in mathematics, computer science, or related subjects.
Responsibilities:
- Conduct research on NSF-funded projects that focus on the foundations of machine learning, big data algorithms, and algorithmic reproducibility. Selected students will assist in the preparation of academic materials, including research papers, presentations, and grant proposals. They will also collaborate with faculty and other team members on various research problems within the scope of the project.
Benefits:
- Gain valuable research experience in cutting-edge areas of machine learning and big data.
- Opportunity to work closely with experienced faculty members on NSF-funded projects.
- Competitive stipend and tuition assistance.
- Ideal for students aspiring to pursue an academic career in top-tier research institutions.
Contact Information:
Interested candidates should submit their resume/CV to Prof. Vinodchandran Variyam as soon as possible. Email: vinod@unl.edu
This is a fantastic opportunity for students looking to deepen their expertise in mathematics and computer science, contribute to significant research projects in foundations of machine learning and big data algorithms, and prepare for a future academic career in leading research institutions. We look forward to receiving your application!