Doctoral courses earlier semesters

• Advanced Statistical Inference, 15 ECTS, Jun Yu, February 2022.
• Abstract Polytopes, Groups and Incidence Geometries, 5 ECTS, Dimitri Leemans, March 2022.
• Differential Geometry, 7.5 ECTS, Per Åhag, August 2022.
• Mathematical Ecology, 7.5 ECTS, Åke Brännström, September 2022

• Advanced Statistical Inference II, 7.5 ECTS, Jun Yu, January 2021.
• Optimisation on Manifolds, 7.5 ECTS, Per Åhag, February 2021.
• Fundamental Mathematical Models in Evolution, 7.5 ECTS, Eric Libby, April 2021.
• Stationary Stochastic Processes, 9 ECTS, Jun Yu, April 2021.
• Experimental Mathematics with Computers, 5 ECTS, Klara Stokes,

• Advanced Probability Theory, 7.5 ECTS, Jun Yu.
• Machine Learning, 7.5 ECTS, Armin Eftekhari.
• Advanced Statistical Inference I, 7.5 ECTS, Jun Yu

Partial differential equations - Åke Brännström
Advanced algebra - Gerold Jäger
Mathematical Biology - Åke Brännström
Study circle on the book "Theoretical Foundations of Functional Data Analysis, with an introduction to Linear Operators" by Hsing and Eubank - Sara Sjöstedt de Luna
Short course on how to do/give a poster presentation - David Cohen

Random geometric graphs - Amites Sarkar & Victor Falgas Ravry
Integration theory - Per Åhag
Wavelet methods in statistics and signal processing

Numerical methods for SDE - David Cohen & Michael Tretyakov
Classical random graphs - Klas Markström
Large networks and general random graphs - Victor Falgas-Ravry
Functional analysis - Klas Markström
Combinatorial number theory - Victor Falgas-Ravry
Advanced statistical modeling - Natalya Pya
Compressive Sensing - Zhiyong Zhou & Jun Yu
Statistical learning with sparsity - Zhiyong Zhou & Jun Yu
Big data and analysis of high dimensional data - Patrik Rydén

Real analysis - Per Åhag
Discret modeling - Gerold Jäger
Analysis on manifolds - Per Åhag
Graph theory - Roland Häggkvist
Asymptotics - Klas Markström
Statistics for spatio-temporal data - Ottmar Cronie & Sara Sjöstedt-de Luna
Advanced probability theory - Jun Yu