Download Job description and selection criteria

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Pandemic wikipedia , lookup

Cross-species transmission wikipedia , lookup

Syndemic wikipedia , lookup

Transcript
DEPARTMENT OF ZOOLOGY
TINBERGEN BUILDING
SOUTH PARKS ROAD OXFORD OX1 3PS
Tel: 01865 271278
Job description and selection criteria
Job title
Senior Post-Doctoral Researcher: Evolutionary and
Computational Analysis of Infectious Disease (Phylodynamics)
Division
MPLS
Department
Zoology
Location
Evolution & Infectious Disease Group, Tinbergen Building,
Department of Zoology, University of Oxford, South Parks Road,
Oxford, OX1 3PS
Grade and salary
Grade 8: £37,756 to £45,053 per annum including a discretionary
range to £49,216 per annum
Hours
Full time
Contract type
3 years (36 months)
Reporting to
Professor Oliver Pybus, Evolution & Infectious Disease Group
Vacancy reference
114048
Additional
information
1
Introduction
The University
The University of Oxford enjoys an international reputation as a world-class centre of
excellence in research and teaching. It employs over 10,000 staff and has a student
population of over 21,000. Our annual income in 2010/11 was £919.6m. Oxford is one of
Europe's most innovative and entrepreneurial universities: income from external research
contracts exceeds £376m p.a., and more than 70 spin-off companies have been created.
For more information please visit www.ox.ac.uk
About the Mathematical, Physical, and Life Sciences Division
The Mathematical, Physical, and Life Sciences Division (MPLS) is one of the four academic
divisions within the University. It comprises ten academic departments: Chemistry,
Computing Laboratory, Earth Sciences, Engineering Sciences, Materials, the Mathematical
Institute, Physics, Plant Sciences, Statistics, Zoology. The constituent units of the Division
enjoy an international reputation for excellence in the mathematical, physical, and life
sciences, as well as in interdisciplinary areas, particularly at the interface with the medical
and environmental sciences.
For more information please visit www.mpls.ox.ac.uk
The Department
The Department of Zoology, within the Mathematical, Physical and Life Sciences Division at
the University of Oxford, has a long-standing reputation for world class research and
teaching. The Department participates in teaching a B.A. degree in Biological Sciences. We
were awarded full marks, 24 out of 24, in the official Subject Review. The Department of
Zoology currently has approximately 70 academic staff and also houses a very large and
interactive group of post docs (~100) and graduate students (~150). Ten members of the
Department are Fellows of the Royal Society including Lord May, President (2000-2005).
For more information about the department, please visit http://www.zoo.ox.ac.uk
The Evolution & Infectious Disease Group
The Evolution & Infectious Disease Group, led by Prof. Oliver Pybus, investigates the
evolutionary, epidemiological and spatial dynamics of infectious diseases. The group has a
particular focus on rapidly-evolving viruses and works with a international network of
collaborators. It also develops phylogenetic, phylodynamic and population genetic methods
for the analysis of pathogen genome data. The group has recently been awarded a 5-year
ERC investigator grant to expand its work.
For more information about the group, please visit http://evolve.zoo.ox.ac.uk.
2
Job description
Research topic
Evolutionary and Computational Analysis of Infectious
Disease (Phylodynamics)
Principal Investigator
/ supervisor
PI: Professor Oliver Pybus
Funding partner
The funds supporting this research are provided by the ERC.
Recent publications
See http://evolve.zoo.ox.ac.uk for details
Technical skills
See Essential/Desired criteria, below
Overview of the role
NOTE: This position is being advertised in parallel with a Postdoctoral Researcher
(Grade 7) position in the same group. Please read the selection criteria for both
positions. If you wish to be considered for both positions please say so in your
application.
We seek an accomplished post-doctoral scientist with a track record of excellence to
undertake research at the interface of evolutionary biology, infectious disease, computational
statistics, and genomics. Candidates will be expected to have computer programming
experience (see Selection Criteria). Highly-motivated researchers with a background in a
science other than biology are also eligible to apply. The position is available immediately for
3 years (36 months). The candidate will join a dynamic and award-winning research group
under the supervision of Professor Oliver Pybus and funding is available to support training,
collaborative visits and conference attendance.
The rapid evolution of many pathogens, particularly viruses, means that their molecular
evolution occurs on the same timescale as their ecological dynamics. As a result many
important problems, such as the surveillance of emerging epidemics or the evolution of
drug/immune resistance, require the use of methods and concepts from a range of
disciplines, including phylogenetics, population genetics, mathematical ecology,
computational immunology, statistics, and genomics. Theoretical and applied research in
this rapidly-growing and inter-disciplinary field is called pathogen phylodynamics.
Two factors have contributed to the increasing importance and scope of phylodynamics.
First, exponential improvements in the affordability of genetic sequencing have led to an
explosion in the number, size and taxonomic range of data sets available for phylodynamic
analysis. Second, growth in computer processing power has enabled the use of increasingly
sophisticated computational methods, most notably Bayesian statistical inference.
3
However it is clear that the growth in pathogen genetic data is outpacing the development of
methods for its analysis. The ERC-funded project PATHPHYLODYN aims to address this
problem by testing and applying new frameworks of evolutionary analysis. It is directed
towards the kind of data sets that will be commonplace in coming years, and to novel forms
of genetic data for which no formal models or statistical methods currently exist. These
include high-coverage sequencing of viral populations sampled sequentially through time,
well-studied infection cohorts, and host immune cell receptor diversity. The project will
encompass a broad range of questions, for example:
(i)
How can we measure natural selection in data sets comprising many thousands
of pathogen genomes, and how does this adaptation relate to viral protein
structures?
(ii) How accurately can we infer virus transmission from very large sets of viral
genomes? And how do we formally integrate viral genetic data with other
sources of information, such as public health surveillance reports, host
demographics, and social network data?
(iii) How can viral genomics be used to predict the outcome of HIV and hepatitis C
virus infection, or the success of anti-viral drug therapy?
(iv) Can we measure and model the dynamics through time of B-cell somatic genetic
diversity?
Research will be guided by two principles. First, questions are to be led by empirical data
(rather than being theoretical in nature). Second, new analysis methods will be grounded in
rigorous statistical inference and based on evolutionary and population dynamic models of
virus and their hosts. Bioinformatic skills are important to the project but the research is not
motivated by bioinformatic or computational questions. A range of pathogens will be
investigated, including but not limited to HIV, hepatitis viruses, influenza viruses, Dengue
virus, rabies virus, West Nile virus, viral disease of wildlife and possibly some bacterial
species.
Responsibilities/duties
1.
2.
3.
4.
5.
6.
7.
8.
9.
Undertake innovative research in the fields of virus evolution, epidemiology, statistical
inference, genomics, population genetics, phylogenetics, quantitative immunology, or
mathematical modelling.
Develop and implement new computational and statistical methods. Create, test and
use relevant computer code; maintain and distribute completed software.
Contribute and develop ideas for new research projects and share responsibility for
shaping the research group’s plans.
Carry out collaborative projects with colleagues in partner institutions, and research
groups.
Regularly write and lead the publication of research findings in international peerreviewed journals and other publications.
Present papers at national conferences, and lead or organise seminars to
disseminate research findings.
Organise and delegate work to other members of the group. Provide scientific advice
and support for other group members. Manage own area of a larger research budget.
Liaise with funding bodies and provide information to project stakeholders and, where
necessary, represent the research group at external meetings/seminars, either with
other members of the team or alone.
Contribute to other tasks within the group and department that fall within the remit of
the funded project.
4
Selection criteria
Essential
 A doctoral degree in a relevant field of biology; or a doctoral degree in another science
(e.g. computer science, statistics, mathematics, physics, chemistry) with a strong
interest in the research described here. Post-qualification research experience.
 Experience of and demonstrated competence in scientific computing using at least one
programming language (C, C++, JAVA, R are preferred).
 Excellent analytical and quantitative skills, including a good working knowledge of
probability theory/statistics.
 Strong publication record.
 Ability to independently plan, manage and develop research projects.
 Excellent communication skills, including the ability to write for publication, present
research proposals and results, and represent the research group at meetings.
Desirable
 An interest in any of: statistical inference, stochastic processes, phylogenetic or
population genetic theory, infectious disease. Expertise in developing models or
methods in any of these areas.
 A theoretical and practical understanding of software for phylogenetic and/or
population genetic analysis of gene sequence data.
 Experience of viral or bacterial evolution and/or molecular epidemiology.
 Expertise in a second computer programming language or mathematical platform.
Working at the University of Oxford
For
further
information
about
working
http://www.ox.ac.uk/about_the_university/jobs/research/
at
Oxford,
please
see:
How to apply
If you consider that you meet the selection criteria, click on the Apply Now button on the
‘Job Details’ page and follow the on-screen instructions to register as a user. You will then
be required to complete a number of screens with your application details, relating to your
skills and experience. When prompted, please provide details of three referees and indicate
whether we can contact them at this stage. You will also be required to upload a CV and
supporting statement. The supporting statement should describe what you have been doing
over at least the last 10 years. This may have been employment, education, or you may
have taken time away from these activities in order to raise a family, care for a dependant, or
travel for example. Your application will be judged solely on the basis of how you
5
demonstrate that that you meet the selection criteria outlined above and we are happy to
consider evidence of transferable skills or experience which you may have gained outside
the context of paid employment or education.
Please save all uploaded documents to show your name and the document type.
All applications must be received by midday on the closing date stated in the online
advertisement.
Should you experience any difficulties using the online application system, please email
[email protected]
To return to the online application at any stage, please click on the following link
www.recruit.ox.ac.uk
Please note that you will be notified of the progress of your application by automatic e-mails
from our e-recruitment system. Please check your spam/junk mail regularly to ensure that
you receive all e-mails.
6