Research Experience Placements
NERC has funded two placements for undergraduates this summer. Apply here.
CEH is seeking applications for two summer undergraduate research experience placements listed below. The placements pay a stipend of £200 per week and last between 8 and 10 weeks, finishing before the end of September. There will be additional funding for project expenses.
To apply, please e-mail the supervisor listed for each project with a covering letter and copy of your CV by the 6th July.
To be eligible, you must be:
• Be studying for an undergraduate degree in a quantitative discipline outside of NERC’s scientific remit (e.g. mathematics, statistics, computing, engineering,physics).
• Be applying for a placement in a different department to their undergraduate degree.
• Be undertaking their first undergraduate degree studies (or integrated Masters).
• Be expected to obtain a first or upper second class UK honours degree.
• Be eligible for subsequent NERC PhD funding (i.e. UK, EU or right to remain in the UK).
Quantifying the information content of ecological models
hosted by Nick Isaac, Centre for Ecology and Hydrology, Wallingford, [email protected])
Ecologists have gathered large quantities of data and a diverse set of tools for analysing them. Increasingly, we have multiple sources of data about the same quantity of interest. For example, both systematic surveys and unstructured occurrence records contain data on species distributions. The former may be higher quality, but the latter has a greater quantity of data. This presents challenges for modelling: which data set should we choose? Can we combine these data? You will create "integrated" hierarchical state-space models of UK pollinator distributions based on systematic surveys and unstructured occurrence records. Models would be constructed using existing data, but in order to become familiar with the data being collected, the student will spend a minimum of one week with the field team conducting PoMS surveys. You will use computer simulations to derive rules of thumb for integrating structured and unstructured datasets for distribution modelling.
Exploiting high spatial resolution radar time series to identify and map vegetation types in Shimoga, India
hosted by Frances Gerard, Centre for Ecology and Hydrology, Wallingford, e-mail: [email protected]).
A Global Change Research Fund Project is investigating the environmental and human drivers of Kyasanur Forest disease (KFD), an emerging vector borne disease in India. An important hypothesis is that changes in the landscape structure are facilitating the spread and exposure risk of this disease. You will explore the use of Sentinel-1 radar time-series data for identifying and mapping different vegetation types of the region. Your will work with sentinel-1 data, develop and implement classification algorithms, compare radar derived maps with existing Landsat TM maps, and interact with collaborators on the project.
Click here to apply for either placement.
NERC has funded two placements for undergraduates this summer. Apply here.
CEH is seeking applications for two summer undergraduate research experience placements listed below. The placements pay a stipend of £200 per week and last between 8 and 10 weeks, finishing before the end of September. There will be additional funding for project expenses.
To apply, please e-mail the supervisor listed for each project with a covering letter and copy of your CV by the 6th July.
To be eligible, you must be:
• Be studying for an undergraduate degree in a quantitative discipline outside of NERC’s scientific remit (e.g. mathematics, statistics, computing, engineering,physics).
• Be applying for a placement in a different department to their undergraduate degree.
• Be undertaking their first undergraduate degree studies (or integrated Masters).
• Be expected to obtain a first or upper second class UK honours degree.
• Be eligible for subsequent NERC PhD funding (i.e. UK, EU or right to remain in the UK).
Quantifying the information content of ecological models
hosted by Nick Isaac, Centre for Ecology and Hydrology, Wallingford, [email protected])
Ecologists have gathered large quantities of data and a diverse set of tools for analysing them. Increasingly, we have multiple sources of data about the same quantity of interest. For example, both systematic surveys and unstructured occurrence records contain data on species distributions. The former may be higher quality, but the latter has a greater quantity of data. This presents challenges for modelling: which data set should we choose? Can we combine these data? You will create "integrated" hierarchical state-space models of UK pollinator distributions based on systematic surveys and unstructured occurrence records. Models would be constructed using existing data, but in order to become familiar with the data being collected, the student will spend a minimum of one week with the field team conducting PoMS surveys. You will use computer simulations to derive rules of thumb for integrating structured and unstructured datasets for distribution modelling.
Exploiting high spatial resolution radar time series to identify and map vegetation types in Shimoga, India
hosted by Frances Gerard, Centre for Ecology and Hydrology, Wallingford, e-mail: [email protected]).
A Global Change Research Fund Project is investigating the environmental and human drivers of Kyasanur Forest disease (KFD), an emerging vector borne disease in India. An important hypothesis is that changes in the landscape structure are facilitating the spread and exposure risk of this disease. You will explore the use of Sentinel-1 radar time-series data for identifying and mapping different vegetation types of the region. Your will work with sentinel-1 data, develop and implement classification algorithms, compare radar derived maps with existing Landsat TM maps, and interact with collaborators on the project.
Click here to apply for either placement.