Post-doctoral Research associate in modelling in
Biology Systems 59238-096.
(aka Post-doctoral Research associate in
A 2 yr PDRA post is available now (ideally starting
asap or at least before April 2007) in the Systems Biology (EPSRC
critical mass grant IPCR).
Although priority will be given to spatial modelling of the
cytoskeleton (actin networks), candidates with appropriate skills will
be considered for any of our other projects outlined below. Our
projects are all
interdisciplinary with strong links to experimental groups. Interested
should apply (full CV), stating in a covering letter their interests
and outlining their previous work and skills.
Scientific queries can be addressed to David
biology) or Nigel
Burroughs (Cytoskeleton, T cells), administrative queries to Brent Kiernan (the systems
simulation: pushing a bead
of Neurospora crassa
(Young et al 2001)
The following projects are representative, additional information on
some areas can be found on the IPCR
1. Cytoskeletal dynamic networks.
We have developed a discrete simulation model
above) that qualitatively reproduces observed actin networks that are
generated behind suitably treated polystyrene beads and some bacteria
(listeria) in cell extracts and live cells. These so called comet tails
propel the object. The simplest explanation for the movement is a
racheting mechanism where thermal/diffusive fluctuations are
rectified by polymerisation of actin fibers at the surface of the
obstacle. However our simulations indicate stress is built up in
the network suggesting that cooperative gel type characteristics are
appearing in the network. A key aim is to capture essential network
architecture properties in suitable continuum models (PDEs) and thus
acheive macroscopic descriptions of the comet and associated networks.
In a recent development we are
the role of a regulator (VASP) in modulating the balance of tethered to
fibers that appears to dramatically affect the network structure.
are a mix of stochastic differential equation (or Fokker-Planck
and continuum models (ODE, PDE and integro DE). Experience with
continuum models (eg elasticity,
liquid crystals), statistical mechanics, stochastic modelling
and/or large scale simulation will be advantageous.
Other projects where we may appoint if suitable candidates apply.
2. Network inference:
methodology and algorithm development. We have an
suite of algorithms for time series analysis of dynamical systems and
fitting of stochastic models using Markov chain Monte Carlo methods.
The algorithms are based on Brownian bridges using hidden variable
paths between time points. This
has allowed us to quantify transcription kinetics through analysis of
fluctuations. This is a rapidly emerging area of great importance as
fluorescent reporters become increasing more sophisticated and
inferring parameters from such data is liable to dominate systems
biology in the coming decade. The project will involving developing
such methods to network inference and applying these on a variety of
data sets from associated plant and eukaryotic cells (eg NFkB)
3. Data integration:
methodology and algorithm development. Data
is a significant problem in systems biology. Key issues are the
with bioinformatics data and data bases, and the inference on mixed
sets (eg micro arrays and proteomics). Developing suitable models and
will be carried out. Experience with MCMC and bioinformatics will be
4. Experimental design of
differential bleaching Fluorescence
Spatial aspects of cellular regulation can be measured using
tagged molecules. Bleaching, or the local distruction of the
can be used to unravel reaction kinetics and diffusion. We are
the identifiability of models given this type of data and using
design to examine how to optimise information. Experience with
experimental design, MCMC, sDEs and PDEs will be advantageous.
5. T cell signalling. An
ongoing IPCR project with links to a model
and analysis programme on the Natural Killer cell synapse.
6. Plant systems biology. In
collaboration with HRI
a number of projects are being initiated including leaf senescence
death), plant-pathogen interactions and flowering. the projects are
driven using microarrays and associated high throughput gene/protein
techniques. the focus is the determine regulatory networks for these
Candidates should have a relevant PhD (statistics, mathematics,
computer science or similar) and a skills appropriate for one or more
of the areas, eg modelling in stochastic or deterministic systems,
(such as MCMC), programming in C/C+, python or a similar
Experience with biological applications is unnecessary but a
to communicate with biologists is essential.
The computer environment includes linux clusters and
Applications should be made to the Personnel Office,
University of Warwick, Coventry CV4 7AL quoting Ref 59238-09 and
the following: 1) completed
application form, 2) academic CV and 3) application letter
relevant experience and interests. Closing date 25th Oct 2006. The
date is flexible, ideally before April 07. Interviews late Oct/early
The appointment is funded by EPSRC/BBSRC.