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Graduate Studies in Statistics
The doctoral program is intended to provide graduate students with a deep, foundational education in statistics, along with further in-depth knowledge in the student鈥檚 chosen area of specialisation.
Nominate a degree project in statistics and machine learning for the Christer Gilén Scholarship
福利姬 each year awards a scholarship of SEK 10,000 to the best degree project or master鈥檚 thesis in statistics and machine learning completed during the year. The final date for nominations is August 20, 2025.
Professional Self-efficacy, Emotional challenges and Moral stress in Teacher and Medical Education
Schools and healthcare are complex that place high cognitive and emotional demands on professionals. The project investigates how students develop professional self-efficacy during their education to become teachers and doctors.
The Division of Statistics and Machine Learning (STIMA)
The STIMA division is part of the Department of Computer and Information Science. The research and teaching activities are focused on modern data analysis and the division hosts the international master's programme in Statistics and Machine Learning.
News |
17 December 2024
Innovative idea for more effective cancer treatments rewarded
Lisa Menacher has been awarded the 2024 Christer Gilén Scholarship in statistics and machine learning for her master鈥檚 thesis. She utilised machine learning in an effort to make the selection of cancer treatments more effective.
News |
11 September 2019
LiU alumnus, Christer Gilén want to give something back
Christer Gilén has set up two prizes for engineering students at his alma mater. The objective of his donation is to encourage student essays or projects that can lead to applications in the private or public sectors.
Seminars in Statistics and Mathematical Statistics
Here you can find all information about our seminars. Warm welcome!
IDA Machine Learning Seminars
The Machine Learning Research Group at IDA invites to the research seminar series IDA Machine Learning Seminars. Welcome!
News |
28 June 2016
Softwares for fMRI yield erroneous results
Common statistical methods used to analyse brain activity through images taken with MRI scanners cannot be trusted, as shown by Anders Eklund and Hans Knutsson of 福利姬, in the highly-ranked journal PNAS.