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Date: Fri Dec 2 03:13:33 2016
Subject: 16.12.02 PhD scholarships in computational biophysics and protein structure modelling, Perth, Australia
The Biomolecular Modelling Group at Curtin University (Perth, Australia)
has two PhD scholarships available for two different projects as outlined
below in (1) understanding protein translation in the ribosome, and (2) the
prediction of new fungal effector-like proteins. These PhD positions are
available immediately.

means by which microbial pathogens thrive is through the externalisation of
effectors, which are imported into host cells, interfere with their
biological processes and promote disease. The discovery of effectors is of
high importance to agriculture, facilitating the screening of cultivars for
disease resistance; however, this is not a simple process. Fungal effector
proteins exhibit little to no amino acid sequence homology to other known
proteins. There is, however, growing evidence that some types of effector
proteins share similar 3D structures despite having very different amino
acid sequences. This project will shed much necessary light into these
effector proteins through the following specific aims: (1) augment existing
bioinformatics pipelines to predict the 3D structure of fungal protein
effectors from publicly available fungal and plant genome/proteome
datasets; (2) discover new fungal effector-like proteins through searching
for similar 3D structures to known effectors; and (3) discover and
characterise new effector-like proteins through the prediction of their
interactions with target plant proteins. This project will be co-supervised
by Prof. Ricardo Mancera (R.Mancera^-^; School of Biomedical
Sciences and Curtin Institute for Computation) and Dr. James Hane
(James.Hane^-^; Centre for Crop and Disease Management,
Department of Environment & Agriculture) at Curtin University. This project
would suit someone with an undergraduate and/or Masters degree in biology,
bioinformatics, biotechnology, chemistry or related field with demonstrable
experience in bioinformatics and/or molecular modelling.

translation, amino acids are brought to the ribosome by transfer RNA (tRNA)
molecules through a diffusive process. Consequently the time that a
ribosome spends at a specific codon is mainly determined by the time that
the cognate tRNA needs to arrive, ultimately governing the speed at which
the ribosome can advance along the mRNA and, therefore, the rate at which
the specific protein is produced. Mathematical models of the process of
translation represent mRNA as a one-dimensional lattice, with each site of
the lattice representing a codon of the mRNA. Ribosomes are represented as
particles that can bind to the lattice, hop stochastically along the
lattice, and hop off the lattice at the last site, all at different rates.
The internal mechanochemical cycle of the ribosome and the fact that all
mRNAs in the cell share the same pool of main translation resources, such
as tRNAs and ribosomes, is also considered. These models, however, neglect
to incorporate the effect that the crowded environment in the cell
cytoplasm has on the diffusion of tRNAs to the ribosomes. As a consequence,
normal diffusion assumptions underlying the estimation of average waiting
times associated to each codon are not valid in general, and it remains
largely unclear how the control of timing of protein synthesis and
regulation of protein production rates are affected. Increasing our ability
to accurately model the underlying mechanisms that govern translation
dynamics will impact the use of recombinant gene expression in
biotechnology to produce a range of therapeutic agents as well as our
understanding of certain diseases arising from malfunctioning of the
regulation mechanisms of translation. This project will focus on how to
describe the hopping rates along the mRNA in a more accurate manner: since
tRNAs cannot freely diffuse in the cytoplasm, the average time spent by a
ribosome on a codon cannot be assumed to be proportional to the
corresponding tRNA concentration. Molecular dynamics and Brownian
simulations of the effects of macromolecular crowding on the diffusion of
tRNAs will improve the modelling of hopping rates, going beyond the
oversimplified assumption that they are constant and proportional to tRNA
abundance. This project will be co-supervised by Prof. Ricardo Mancera
(R.Mancera^-^; School of Biomedical Sciences and Curtin
Institute for Computation) and Dr. Maria Carmen Romano
(M.Romano^-^; Institute for Complex Systems and Mathematical
Biology, Department of Physics, University of Aberdeen, UK). The student
will be expected to spend the first six months of this project at Aberdeen
(UK), followed by two years in Perth (Australia), and then a further 6
months at Aberdeen to complete the project. This project would suit
someone with an undergraduate and/or Masters degree in physics, chemistry,
biotechnology or related field with demonstrable experience in molecular
dynamics simulations.

For both PhD positions the student will be required to apply for admission
and enrol at Curtin University ( Curtin is the
largest university in Western Australia and is ranked amongst the top
universities in Australia and within the top 2% in the world. The
Biomolecular Modelling Group, headed by Prof. Ricardo Mancera, is one of
the major users of the newly established Pawsey Supercomputing Centre in
Perth, which houses the fastest supercomputer in the southern hemisphere.
In addition, living in the state capital Perth offers a great lifestyle due
to Western Australias superb weather, beaches and outdoors activities. For
project 2 the student will also be expected to apply for admission and
co-enrol at the University of Aberdeen ( Aberdeen is
one of the oldest universities in the UK and ranked within the top 1% in
the world.

Applicants whose academic qualifications were not obtained from an English-
language speaking country will need to satisfy English language
requirements by attaining 7.0 in all bands of the IELTS or an overall score
of 94 in the TOEFL (with a minimum of 27 in writing and 24 in other areas).
Only applicants that fulfil these requirements need apply by submitting a
copy of their full CV to Professor Ricardo Mancera
(R.Mancera^-^, including full details of all academic degrees
obtained, research skills and experience, any publications and conference
presentations, and the names of 2-3 referees.

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