Bringing life science professionals together and furthering skills in the scientific community are in SciLifeLab’s DNA. Our many events and courses, which span a wide range of topics, present opportunities to develop your know-how and share your own experiences and network – sparking new ideas, as well as new collaborations.
Contact
events@scilifelab.se
education@scilifelab.uu.se
If you are part of the SciLifeLab community, you can submit an event to this calendar.
This workshop provides resources to advanced tools for analysis of spatial datasets via a series of online lectures and computer practicals. The total course duration is 40 hours, including the online lectures and practical coding workshop that will be held online.
National workshop open for PhD students (prioritized), postdocs, researchers and others from all Swedish universities who have previously participated in the NBIS Tools for reproducible research course or with demonstrated experience in writing Snakemake workflows.
This course aims to help researchers to visualize their data in different ways using R, and will also aim to show researchers how they can make publication grade figures using R
The summer school is aimed at graduate students, post-docs, and young independent investigators who want to learn about new techniques to explore the proteins encoded by the human genome. The course will teach state-of-the-art analysis of the human proteins with a focus on antibody-based methods, transcriptomics and mass spectrometry. The course will have several daily lectures […]
National course open for PhD students, postdocs, researchers and other employees in need of biostatistical skills within all Swedish universities. The course is geared towards life scientists wanting to be able to understand and use basic statistical methods. It would also suit those already applying biostatistical methods but have never got a chance to reflect on and truly grasp the basic statistical concepts, such as the commonly misinterpreted p-value.
This intense one-week workshop provides an introduction to the analysis of next generation sequencing data. Lectures on the theory of concepts will be paired with practical computational exercises in the Linux environment. The practical exercises will focus on data from the Illumina platform, but we will discuss other sequencing platforms and the advantages and challenges to using their data during the lectures.
National course open for PhD students, postdocs, researchers and other employees in need of fundamental Python skills within all Swedish universities
The purpose of the course is to prepare and train Cryo-EM facility users in sample preparation methods, introduce users to the image data acquisition workflow, expand knowledge about cryo-EM methods among researchers and show that everyone can learn how to use cryo-EM for structure and cell biology. The course is open for facility users or […]
National course open for PhD students, postdocs, researchers and other employees within all Swedish universities. This course will introduce important aspects of Research Data Management through a series of lectures and hands-on computer exercises. The course is intended for researchers that want to take the first steps towards a more systematic and reproducible approach to analysing and managing research data.
National workshop open for PhD students, postdocs, researchers and other employees within Swedish academia. This course is run by the National Bioinformatics Infrastructure Sweden (NBIS).
TEM sample preparation course – Chemical fixation, high pressure freezing, plastic embedding and staining methods including practice on ultra-microtome sectioning, TEM imaging and an introduction to CLEM (Correlative Light and Electron Microscopy), FIB-SEM (Focused Ion Beam) and electron tomography. Pre-requisite criterion: Basic EM course at UCEM or equal previous experiences of EM methods. Participants will […]
This course is open for PhD students, postdocs, group leaders and core facility staff interested in making their computational analysis more reproducible.