We have two PhD/Postdoc positions in machine learning and data mining for personalized cancer screening at Simula Metropolitan Center for Digital Engineering (SimulaMet), Oslo, Norway. The positions are available as a part of the Norwegian-funded research project DeCipher in collaboration between SimulaMet, Cancer Registry of Norway, Lawrence Livermore National Laboratory (LLNL), and Karolinska University Hospital. The project combines the unique Norwegian and Swedish registry data from more than 2 million individuals including extensive screening histories and epidemiological expertise, with LLNL’s exceptional HPC computing infrastructure, data analysis and modelling experience, and with Simula’s expertise in machine learning methodology.
The DeCipher project aims to develop a data-driven framework to provide a personalized time-varying risk assessment for cancer initiation and identify subgroups of individuals and factors leading to similar disease progression. Specifically, the following sub-projects will be investigated:
- Development of matrix factorization approaches for reconstruction of individualized disease trajectories from longitudinal screening data.
- Development of data fusion approaches based on matrix and tensor factorizations for joint analysis of longitudinal screening data and lifestyle information as well as other relevant health data.
Application deadline: December 01, 2019.
Interested candidates can learn more about the project and submit their applications through the application portal:
https://www.simulamet.no/about/job/call-phd-and-postdoc-fellows-develop-machine-learning-approaches-personalized-cancer
