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BBSRC iCase 4 Year PhD Studentship

Posted by , on 10 February 2017

Closing Date: 15 March 2021

Decoding the network logic for resetting pluripotency – Collaborative Stem Cell Research PhD Studentship with Microsoft Research – re-advertised, revised closing date 31st March 2017

Outline Project Description:

  • Interdisciplinary project at the interface of stem cell research and computational modelling
  • Delineation of network trajectories for cellular reprogramming at single cell resolution
  • Combination of wet lab research with logical modelling
  • Collaboration between the laboratory of Prof. Austin Smith and Microsoft Research Cambridge

 

The Smith Group at the Medical Research Council Wellcome Trust Stem Cell Institute in Cambridge in partnership with the Computational Biology Group at Microsoft Research offers an exciting interdisciplinary 4-year PhD studentship commencing October 2017.
The pluripotent ground state of embryonic stem cells (ESCs) is governed by a self-reinforcing interaction network of transcription factors (Dunn et al, Science 2014). Combinations of factors within this network can induce somatic cells to acquire pluripotency, a process called molecular reprogramming (Takahashi and Yamanaka, Cell, 2006). Experimental and computational efforts have led to circuitry mapping of the key players in maintenance of the ESC state. However, how this molecular circuitry is launched and fully connected during reprogramming remains unclear.

 

This project is a cross-disciplinary investigation to address systematically how cells transit to the pluripotent ESC state at the molecular network level. The multi-step, heterogeneous and asynchronous nature of the reprogramming process presents technical challenges. This project is designed to overcome these challenges by using a minimal reprogramming system and integrating quantitative single-cell gene expression profiling at defined reprogramming stages with computational network synthesis and modelling. This approach will transform a temporal series of single-cell snapshots of network status into reconfiguring network trajectories. Predictions formulated from the synthesised trajectories will be tested experimentally and the results used for iterative refinement of the model set.
As part of the BBSRC doctoral training programme, this 4-year PhD contains tailored training courses in the first six months of the studentship. In addition, a key element of this project is that the student will spend three months at Microsoft Research Cambridge, under the supervision of our collaborator, Dr Sara-Jane Dunn, to develop wider training and skills.
For further details about our group and the institute, please visit:http://www.stemcells.cam.ac.uk/ 

Funding Notes

UK and EEA students who have, or are expecting to attain, at least an upper second class honours degree (or equivalent) in relevant biological subjects are invited to apply. The interdisciplinary nature of the project means that we welcome applications from students with mathematical and computing experience who are interested in using their skills to address biological questions.

 

Application details are available at http://www.stemcells.cam.ac.uk/study/otheropportunities/#BBSRC. Please ask your referees to submit references directly to the SCI Graduate Administrator: sci-phd@stemcells.cam.ac.uk, using “BBSRCiCASE student reference” in the subject header. The deadline is 31st March 2017 and shortlisted candidates will be interviewed in April. Please note: this studentship is being re-advertised. Previous applicants need not apply.

References

Dunn, S. J., Martello, G., Yordanov, B., Emmott, S. & Smith, A. G. Defining an essential transcription factor program for naïve pluripotency. Science 344, 1156-1160, (2014).
Martello, G. & Smith, A. The nature of embryonic stem cells. Annu Rev Cell Dev Biol 30, 647-675, (2014).
Yordanov, B., Dunn, S.-J., Kugler, H., Smith, A., Martello, G. & Emmott, S. A method to identify and analyze biological programs through automated reasoning. Npj Systems Biology And Applications 2, 16010, (2016)

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