We propose that plant stress responses are mediated by a central regulatory hub, the multiprotein Mediator complex, an evolutionarily conserved co-regulator complex required for transcription of all RNA polymerase II-dependent genes in eukaryotes. Our hypothesis is that Mediator integrates different stress signals to control the expression of genes required for stress acclimation through direct interaction with transcription factors and cis-elements and/or through chromatin remodelling. To reveal the regulatory mechanisms of Mediator and to functionally define stress responses at all organisational levels we will construct a holistic model of plant stress responses by combining multilayer network algorithms and hidden Markov models. Integrating collected experimental data from the different organisational levels – from the input signals, through the receiving mediator subunits and out to the changes in gene expression and the resultant stress response phenotype – will allow us to generate a dynamic and comprehensive model of the complex signalling networks triggered by exposure to stress.
The postdoctoral project is part of the 5-year multidisciplinary project “Decoding Signalling Networks Controlling Plant Stress Responses”, financed by the Swedish Foundation for Strategic Research. The project provides challenging postdoctoral training for multiple postdocs, who will solve problems using methodologies from biology, physics, and computer science, as well as taking advantage of advanced technical platforms in the environment. The successful candidates will collaborate with leading scientists in dynamic and multidisciplinary environments.
A successful candidate will study how the Mediator function as a regulatory hub integrating stress signals originating in different cellular locations to control changes in gene expression required for the acclimation to stress. Specifically, overlapping sets of target genes for specific Mediator modules in different stress conditions and their common mode of regulation contain information about master regulatory mechanisms of stress responses. Using a suit of computational tools, the postdoc will identify modules of co-regulated genes with shared regulatory motifs and gene products with conserved biological functions regarding stress responses.
The position is a two-year full-time employment that will open in January, 2018 (exact date according to agreement).
To qualify for the position, the candidate should have a PhD degree, or a foreign degree that is deemed equivalent, in applied mathematics, bioinformatics, computer science, physics, or relevant field. To be eligible the degree should have been completed a maximum of three years before the end of the application period unless certain circumstances exist.
We are looking for a highly motivated and responsible candidate who is passionate about developing as an individual scientist as well as a research team member. The candidate should have extensive training in statistics or computational modeling with languages such as C++, Python or R, and be passionate about developing machine learning algorithms to address biological questions. Working experience in large-scale sequence analysis is an advantage. An ability to perform research independently as well as in a team, and good skills in the English language, are essential.