Three PhD positions in cross-disciplinary projects (Biochemistry, Statistics, and Computational mathematics)
We announce PhD positions in Biochemistry, Statistics, and Computational mathematics, in two cross-disciplinary projects at Stockholm University. The positions are part of an effort to promote work across department boundaries and are set up to have PhD students coming from different disciplines work in collaboration.
Project 1: Methods for spatial molecular tissue profiling
- 1 PhD student in Biochemistry, with Mats Nilsson
Link to application site: https://www.su.se/english/about/working-at-su/phd?rmpage=job&rmjob=6976&rmlang=UK
- 1 PhD student in Mathematical statistics, with Joanna Tyrcha
Link to application site: https://www.su.se/english/about/working-at-su/phd?rmpage=job&rmjob=6952&rmlang=UK
We are now entering the beginning of a new phase in which massively parallel sequencing is performed directly in the cell. Mats Nilsson’s lab has pioneered a technique called in situ sequencing that detects large numbers of gene transcripts in cells in tissue sections in a targeted way. His lab works with two data sets: one concerns mapping neurons in mouse brains, the other one concerns generating data from breast cancer tumors. The general goal of the project is to answer the question “do some cells/molecules end up in certain spatial location in relation to each other?”
These biological issues pose challenges concerning both statistical data analysis and statistical inference. The methods of spatial statistics are key. Spatial statistics includes a variety of techniques of which many are still in their early development. There is hence a potential to develop new spatial analysis methods to answer biological questions.
Project 2: Computational problems in evolution relating to the role of gene duplications in coevolutionary interactions
- 1 PhD student in Computational Mathematics, with Lars Arvestad
Link to application site: https://www.math.su.se/english/education/phd-studies/research-projects/possible-research-projects-in-computational-mathematics-1.403933
The project is joint with Christopher Wheat at the Zoology department, whom have recently filled a PhD position for this project.
We have in past projects developed models and tools for analyzing gene evolution with respect to species evolution. Using techniques from statistical learning and inference, the PhD candidate will adapt and extend this work for other types of data and new question in evolution. Working with experts on the evolution of Pieridae butterflies and their Brassicales hostplants, we want to address detailed questions regarding the evolutionary history of Pieridae genes, in particular relating to gene duplication and functional innovation. The aim is to better understand the genetic and evolutionary basis of what drives the diversification of much of life on Earth.