Data Science (master's two years)

Data Science and Life Science

This specialization is focused on machine learning, most often deep learning, applied to complex sequence data. Data are typically very high-dimensional, with complex dependencies and data types, meaning that advanced machine learning is typically required to detect any meaningful signals.

The group also has research interest in causality and domain robustness. The data typically reflect molecular data where some prior knowledge is available, which means that architectures can be inspired from domain knowledge. Recently, the group has also developed an interest in machine learning to connect climate change with future health consequences. Tasks range form theoretical machine learning to more applied. The tasks are offered by the Biomedical Informatics group.

Some recent projects:

Predicting cancer and other diseases based on the quantitative adverse outcome pathway concept - developing a Bayesian tool for risk assessment by Torbj?rn Rognes
Machine learning for the greater good: understanding how climate change will affect future health by Geir Kjetil Sandve

Published Oct. 5, 2023 1:51 PM - Last modified Oct. 5, 2023 1:56 PM