The below link will take you to a google form. You will be required to fill in some basic information (e.g., career stage and institution), a self-assessment of your current level of knowledge on statistical methods, and a brief description of your motivation for applying to attend the summer school. Before you apply, make sure to have a look at the practical information.
Applications are closed
There is limited space to attend in-person, so application to the summer school does not guarantee participation. Note that all material used in the summer school will be made available online, after the summer school has been completed. When the application deadline has passed (see dates and deadlines), all applications are collected. If there are more applications than spots, participants will be ranked based on the following criteria:
The ranking will reflect NTNU its vision on diversity and equality, but can generally be expected to prioritize participants that actively seek to apply multivariate statistical methods to data involved in a MSc or PhD project. Postdoc or researcher applicants will be considered, but participants still actively pursuing an MSc or PhD project will be prioritized. Prior knowledge in statistical modeling with GLM(M)s and application of ordination methods is considered an advantage, and some prior knowledge is required to make the most out of the summer school. However, candidates that possess little prior knowledge in statistical modeling, but are willing to face a steep learning curve and learn about related methods on short notice, are also welcome to apply. All participants are expected to be familiar with the R-programming language, and have a working and up-to-date installation of R on their computer upon arrival (preferably with pre-installed relevant packages, more details will be communicated via e-mail before arrival). Participants that are not invited to attend in-person may be invited to attend digitally, if the venue allows for such a solution. Details on the possibility for digital attendance will be made available at a later time.