Postdoctoral Research Assistant
Applications for this vacancy closed on 16 August 2024 at 12:00PM
Applications are invited for a Postdoctoral Research Assistant in Atmospheric
Physics.
Weather and climate prediction involves combining information about the
current state of the Earth-system with a computer model encoding the equations
describing the system. Errors in the approximations made when building the
computer model introduce uncertainty into the prediction. This _model
uncertainty_ must be accounted for to produce reliable forecasts on weather
through climate timescales. In the weather forecasting community, stochastic
parametrisations are a widely used approach to represent this model
uncertainty: random numbers are included into the equations of motion to
account for uncertainty in the model’s formulation. Stochastic
parametrisations are remarkably effective at improving the skill of
probabilistic weather forecasts, but current operational approaches are simple
and pragmatic. This begs the question, why are our current approaches so
effective, and how can we improve them further? This project will address
these important questions
The successful candidate will undertake independent research, and participate
in the academic life of the Atmospheric Processes group and the AOPP sub-
department.
Applicants should possess, or be very close to obtaining, a doctorate in
physics, climate science, computer science, or a related field.
The post-holder will have the opportunity to teach.
Please direct enquiries about the role to Hannah Christensen
(hannah.christensen@physics.ox.ac.uk)
Only applications received before midday 16th August 2024 can be considered.
You will be required to upload a brief statement of research interests, CV and
details of two referees as part of your online application.
Physics.
Weather and climate prediction involves combining information about the
current state of the Earth-system with a computer model encoding the equations
describing the system. Errors in the approximations made when building the
computer model introduce uncertainty into the prediction. This _model
uncertainty_ must be accounted for to produce reliable forecasts on weather
through climate timescales. In the weather forecasting community, stochastic
parametrisations are a widely used approach to represent this model
uncertainty: random numbers are included into the equations of motion to
account for uncertainty in the model’s formulation. Stochastic
parametrisations are remarkably effective at improving the skill of
probabilistic weather forecasts, but current operational approaches are simple
and pragmatic. This begs the question, why are our current approaches so
effective, and how can we improve them further? This project will address
these important questions
The successful candidate will undertake independent research, and participate
in the academic life of the Atmospheric Processes group and the AOPP sub-
department.
Applicants should possess, or be very close to obtaining, a doctorate in
physics, climate science, computer science, or a related field.
The post-holder will have the opportunity to teach.
Please direct enquiries about the role to Hannah Christensen
(hannah.christensen@physics.ox.ac.uk)
Only applications received before midday 16th August 2024 can be considered.
You will be required to upload a brief statement of research interests, CV and
details of two referees as part of your online application.
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Department of Physics, Clarendon Laboratory, Parks Road
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vacancy:applicationClosingDate |
2024-08-16 12:00:00+01:00
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vacancy:applicationOpeningDate |
2024-07-31 09:00:00+01:00
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vacancy:internalApplicationsOnly |
False
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comment |
Applications are invited for a Postdoctoral Research Assistant in Atmospheric
Physics. Weather and climate prediction involves combining information about the current state of the Earth-system with a computer model encoding the equations describing the system. Errors in the approximations made when building the computer model introduce uncertainty into the prediction. This _model uncertainty_ must be accounted for to produce reliable forecasts on weather through climate timescales. In the weather forecasting community, stochastic parametrisations are a widely used approach to represent this model uncertainty: random numbers are included into the equations of motion to account for uncertainty in the model’s formulation. ... Applications are invited for a Postdoctoral Research Assistant in Atmospheric Physics. Weather and climate prediction involves combining information about the current state of the Earth-system with a computer model encoding the equations describing the system. Errors in the approximations made when building the computer model introduce uncertainty into the prediction. This model uncertainty must be accounted for to produce reliable forecasts on weather through climate timescales. In the weather forecasting community, stochastic parametrisations are a widely used approach to represent this model uncertainty: random numbers are included into the equations of motion to account for uncertainty in the model’s ... |
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Postdoctoral Research Assistant
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notation |
174245
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