Postdoctoral Research Associate in Evolution and Bioinformatics
Applications for this vacancy closed on 16 August 2024 at 12:00PM
Working for the Department of Biology you will be responsible for carrying out
research for a Gordon & Betty Moore Foundation grant with aim of understanding
the pathways that control a nascent endosymbiotic interaction between a
protist and green algae.
The project will involve single cell transcriptome, hyper-LOPIT 3D subcellular
proteomics data combined with RNAi approaches to identify how a host cell can
manipulate the fate of its endosymbiotic partner cells. Using these datasets,
we will then apply phylogenomic methods to understand how host control
mechanisms evolve in endosymbiotic interactions. You will have the opportunity
to use a number of established datasets and so must be confident in a range of
bioinformatic approaches. As such the post could be largely a bioinformatic
post or one that combines an equal share of bioinformatic analyses and
laboratory work. You will have the opportunity to collaborate in the
preparation of research publications and presenting papers at conferences or
public meetings.
You will hold, or be close to completion of, a relevant PhD/DPhil, together
with experience. You will possess sufficient specialist knowledge in
bioinformatic methods, running scripts and conducting phylogenomic analyses.
You will have the ability to manage your own academic and associated
activities. Excellent communications skills, including the ability to write
for publications, present research proposals and results, and represent the
research group at meetings is essential.
Where Covid-19 has resulted in substantial disruption to your work or research
outputs, please explain this by providing an additional paragraph in your
supporting statement.
The University of Oxford is committed to equality and valuing diversity. All
applicants will be judged on merit, according to the selection criteria.
This post is full time and available immediately.
The closing date for applications is 12.00 noon on Friday 16 August 2024,
interviews are likely to be scheduled for late August or Early September.
Applications for this vacancy are to be made online via our e-recruitment
system, and you will be required to upload a supporting statement and CV as
part of your online application.
research for a Gordon & Betty Moore Foundation grant with aim of understanding
the pathways that control a nascent endosymbiotic interaction between a
protist and green algae.
The project will involve single cell transcriptome, hyper-LOPIT 3D subcellular
proteomics data combined with RNAi approaches to identify how a host cell can
manipulate the fate of its endosymbiotic partner cells. Using these datasets,
we will then apply phylogenomic methods to understand how host control
mechanisms evolve in endosymbiotic interactions. You will have the opportunity
to use a number of established datasets and so must be confident in a range of
bioinformatic approaches. As such the post could be largely a bioinformatic
post or one that combines an equal share of bioinformatic analyses and
laboratory work. You will have the opportunity to collaborate in the
preparation of research publications and presenting papers at conferences or
public meetings.
You will hold, or be close to completion of, a relevant PhD/DPhil, together
with experience. You will possess sufficient specialist knowledge in
bioinformatic methods, running scripts and conducting phylogenomic analyses.
You will have the ability to manage your own academic and associated
activities. Excellent communications skills, including the ability to write
for publications, present research proposals and results, and represent the
research group at meetings is essential.
Where Covid-19 has resulted in substantial disruption to your work or research
outputs, please explain this by providing an additional paragraph in your
supporting statement.
The University of Oxford is committed to equality and valuing diversity. All
applicants will be judged on merit, according to the selection criteria.
This post is full time and available immediately.
The closing date for applications is 12.00 noon on Friday 16 August 2024,
interviews are likely to be scheduled for late August or Early September.
Applications for this vacancy are to be made online via our e-recruitment
system, and you will be required to upload a supporting statement and CV as
part of your online application.
dc:spatial |
Department of Biology, 11a Mansfield Road, Oxford OX1 3SZ
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vacancy:applicationClosingDate |
2024-08-16 12:00:00+01:00
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vacancy:applicationOpeningDate |
2024-07-08 09:00:00+01:00
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vacancy:furtherParticulars | |
vacancy:internalApplicationsOnly |
False
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vacancy:salary | |
type | |
comment |
Working for the Department of Biology you will be responsible for carrying out research for a Gordon & Betty Moore Foundation grant with aim of understanding the pathways that control a nascent endosymbiotic interaction between a protist and green algae. The project will involve single cell transcriptome, hyper-LOPIT 3D subcellular proteomics data combined with RNAi approaches to identify how a host cell can manipulate the fate of its endosymbiotic partner cells. Using these datasets, we will then apply phylogenomic methods to understand how host control mechanisms evolve in endosymbiotic interactions. You will have the opportunity to use a number ... Working for the Department of Biology you will be responsible for carrying out
research for a Gordon & Betty Moore Foundation grant with aim of understanding the pathways that control a nascent endosymbiotic interaction between a protist and green algae. The project will involve single cell transcriptome, hyper-LOPIT 3D subcellular proteomics data combined with RNAi approaches to identify how a host cell can manipulate the fate of its endosymbiotic partner cells. Using these datasets, we will then apply phylogenomic methods to understand how host control mechanisms evolve in endosymbiotic interactions. You will have the opportunity to use a number of ... |
label |
Postdoctoral Research Associate in Evolution and Bioinformatics
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notation |
173935
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based near | |
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