Training

From SFI

Teaching helps to organize the teacher's thoughts. Mentoring the next generation of scientists is helpful both for them and for the mentors.

University of Oslo Graduate School in Biostatistics

The University of Oslo Graduate School in Biostatistics is an inspiring and productive environment on a high international level for the training of a new generation of biostatistical researchers. The school provides Ph.D.-students with a broad range of courses and workshops in statistics and biostatistics, in order to give them the breadth and depth of knowledge needed to meet the challenges of modern biostatistics.

The graduate school builds on the Ph.D.-programs at the Faculty of Mathematics and Natural Sciences and the Faculty of Medicine at the University of Oslo, and it operates as a joint activity of researchers from different departments and collaborating research groups. The school has staff and students at the Division of Statistics at the Department of Mathematics, the Department of Biostatistics at the Institute of Basic Medical Research, the Biomedical research group at Department of Informatics, and Norwegian Computing Center. Most of the staff and students are affiliated with Statistics for Innovation and with the centre for Biostatistical Modelling in the Medical Sciences.

(sfi)² organises and supports courses and training occasions. Follow the links below for specific information. Most courses require a registration.

Training and Courses

Intensive course on Bayesian inference for the Nordic biostatistics network (BGC)
Helsinki University, 4-8 March and 13-17 May 2013

The course explains the fundamental issues in Bayesian inference, role of prior probabilities, predictive modeling, hierarchical models, model selection, asymptotics. These concepts are also put into several application contexts to demonstrate how and why Bayesian inference works, what are the benefits and potential pitfalls. No prior knowledge about Bayesian inference is expected. The aim is to equip participants with good intuition on how the Bayesian machinery works, rather than focus on exact mathematical formalism.

Lecturer: Professor Jukka Corander, University of Helsinki