Johan Henriksson, group leader at MIMS and the Dept. of Molecular Biology, in close collaboration with Tommy Löfstedt, group leader at the Dept. of Computing Science, are looking for a postdoc.
Gene isoforms play key roles in disease etiology and outcome. Despite that gene isoforms are involved in most biological processes, they are commonly ignored because we lack tools to understand them. In this project we will build new large-scale machine learning tools to extract gene isoform information from commonly existing single-cell RNA-seq data.
The approach we consider is based on variational autoencoders and sequence models. The challenges lie in the data being extremely large, sparse, and noisy. The project will open doors into the currently most rapidly expanding field in biology.
Application deadline: 1 December 2022
You will carry out formulation, implementation and testing of machine learning approaches to model and understand single-cell RNAseq data. You will present your findings, write manuscripts, help supervising students, and actively contribute to a collegial lab culture.
You will be based in the lab of Johan Henriksson (www.henlab.org) in collaboration with the machine learning group of Associate Professor Tommy Löfstedt. The Henriksson lab is based at the Department of Molecular Biology and is part of The Laboratory of Molecular Infection Medicine Sweden (MIMS), which is the Swedish node within the Nordic EMBL Partnership for Molecular Medicine. The project is run in close collaboration with Tommy Löfstedt, docent and associate professor and head of the machine learning group at the Department of Computing Science.
Read the full description and apply here: https://umu.varbi.com/en/?jobtoken=1cd481eb57fc50fca5f772af4d85578679b3a248b