Data Science expertise for the Faculty of Science
Data Science Lab
As of 2018, DIKU is a part of the newly established Data Science Lab (DSL) - an offer for students and researchers at the Faculty of Science (SCIENCE). The aim of the lab is to improve the quality of scientific data analyses in research carried out at the entire faculty.
From January 1, 2018, the Laboratory for Applied Statistics has been expanded to the new Data Science Lab and now includes researchers within both statistics and computer science. The purpose is to support students and researchers at SCIENCE in the area of data analysis through a number of activities. Hopefully, the DSL initiative will contribute to promoting data science throughout the entire Faculty and be a helpful support for students and researchers working with data across a variety of scientific fields.
From DIKU, associate professor Erik Dam and postdoc Akshay Pai contribute with expertise in data science, image and signal anaysis, machine learning, and deep learning applied to challenges from medicine, biomechanics, and biology.
Consultations and cooperation
The DSL researchers will be offering consultations for both students and researchers where they can discuss their data problems.
For the students, the consultations will last approx. 20 minutes and are meant as a supplement to one's own efforts. For researchers at all levels, DSL offers assessment of the potential for data science assistance as well as guidance and room for discussion in relation to analyses and design of experiments.
Furthermore, researchers, institutions and companies outside SCIENCE are also welcome to contact DSL regarding potential collaborations.
Data Science Playground
Every week DSL hosts a "Data Science Playground", where students can work on their project under the supervision of both a statistical and a computer science researcher. For students working on projects this is a good opportunity to receive input/guidance on issues along the way.
Courses and workshops
Furthermore, DSL offers a number of short courses and workshops for researchers such as |and Introduction to Python – as well as various PhD courses.