PhD Positions in Matrix Computations: The inEXASCALE project at Charles University seeks to revolutionize algorithm design and analysis in the exascale era. The research initiative aims to uncover the impact of inexactness in algorithms with a focus on developing fast and provably accurate computation techniques.
Designation: Funded PhD Positions
Research Area: Numerical Linear Algebra, Numerical Analysis, Parallel Computing, Computational/Data Science Applications
Location: Charles University, Prague, Czech Republic
Eligibility/Qualification:
Candidates with a strong background in numerical linear algebra, numerical analysis, parallel computing, or computational/data science application domains are encouraged to apply. Applicants must hold a Master’s degree by February 2025.
Job Description:
Successful candidates will be enrolled in the PhD program at Charles University and will have the opportunity to delve into various research areas including:
- Development and analysis of mixed precision numerical linear algebra algorithms
- Parallel algorithms and implementations for new mixed precision algorithms
- Application of numerical linear algebra in data analysis and machine learning
- Stability and convergence analysis of asynchronous methods
How to Apply:
Interested candidates should submit the following documents to carson@karlin.mff.cuni.cz:
- Curriculum Vitae
- Cover letter explaining motivation and interest in obtaining the position of PhD student
- Brief summary of Master’s thesis (including PDF file of Master’s thesis if available)
Additionally, candidates must arrange for two letters of recommendation to be sent directly to the same email address before the application deadline. Selected finalists will be invited to officially apply through the university system.
Last Date for Apply: October 31, 2024
For further details on the admission procedure and complete information, visit here or direct your inquiries to:
Dr. Erin C. Carson
Department of Numerical Mathematics, Faculty of Mathematics and Physics, Charles University
Sokolovska 83, 18675 Prague
Email: carson@karlin.mff.cuni.cz
Homepage: Link
