Accelerating immunity research through a machine learning software platform
The immune system saves our life from invading viruses and bacterias on a daily basis. Understanding the immune system better also holds promise for improved vaccination, developing new treatments for auto-immune diseases and for developing new strategies to fight cancer. A large amount of medical research is thus directed at improving the detailed understanding of how the immune system recognizes and deals with threats to our body. Recently, machine learning has entered center stage in this research, due to its potential to learn complex patterns and relations. We have here in Oslo recently finalized a first version of an internationally leading, comprehensive software platform to support machine learning-based investigations of the immune system.
The aim of this master project is to develop software solutions to boost such medical research into immunology based on machine learning. The work could range from algorithmic improvement of existing, fundamental components of the mentioned software platform to the development of novel functionalities inspired by the concrete research needs of collaborating medical research groups. We are also interested in novel solutions to improve interoperability, reproducibility and adaptability of such platforms.
No prior knowledge of biology or immunity is needed. A good grasp of either algorithms, software engineering or other aspects relevant for the task is required, and so is a desire to work hard and learn much from the master thesis project.
More details about adaptive immunity, relevant machine learning approaches and the work of our research group is available here.