Modèles de séries temporelles avec applications en finance et assurance
ABG-133378 | Thesis topic | |
2025-09-11 | Public funding alone (i.e. government, region, European, international organization research grant) |
- Mathematics
- Economy, management
- Engineering sciences
Topic description
Professor Yang Lu is looking for PhD students with a strong background in mathematics/statistics or engineering. His personal website is:
https://sites.google.com/site/luyangensae/home/research?authuser=0
interested candidates are invited to look at his personal website before contacting him.
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Concordia University is an English‑language public research university located in Montréal, Québec, Canada, and is consistently ranked as the number 1 university under 50 years in North America . The Department of Mathematics and Statistics has a well-established graduate program in pure and applied Mathematics, Statistics, financial mathematics, as well as actuarial science. Within the department, the lab of Associate Professor Yang Lu conducts research in applied statistics with applications to insurance and finance. Dr. Lu got his PhD in applied mathematics from Universite Paris-Dauphine and is an alumni of Ecole Normale Supérieure de Paris Rue d’Ulm. He has published widely in actuarial science, finance and statistics and has obtained grants from NSERC, SSHRC, FRQNT, Society of Actuaries, Casualty Acruarial Society, among others. His research group is looking for PhD students with strong background in mathematics/statistics or engineering. The PhD program at Concordia lasts 4-5 years and students receive a comprehensive package of funding support. Official information about our graduate program is available at:
https://www.concordia.ca/artsci/math-stats/programs/graduate.html
Applications are due early January each year. In case you are interested in joining Dr. Yang Lu’s group, please be sure to contact him at yang.lu@concordia.ca to discuss research topic and funding opportunities.
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Country where you obtained your PhD
Institution awarding doctoral degree
Candidate's profile
Master 2 or engineering school students with strong background in mathematics/statistics/actuarial science/engineering.
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