New UROP opportunities will be listed here for one month, and thereafter will appear on the relevant faculty page (UROP website) until notified otherwise by the relevant member of academic staff.


NEW OPPORTUNITIES ACROSS COLLEGE
Title of UROP Opportunity (Research Experience) & DetailsExperienced required (if any)Contact Details and any further Information

NEW (18 June 2021)

High Resolution Spectroscopy for Astrophysics: Spectroscopy of astronomical objects is the primary tool for understanding their physical properties, chemistries, and evolution. Spectral features observed with ground- and space-based telescopes are interpreted using computational models that derive many of their parameters from databases of atomic and molecular lines. However, developments in telescopes (such as the planned Extremely Large Telescope, ELT, observatory in Chile) have far outpaced the speed at which atomic data, fundamental for the interpretation of astronomical spectra, can be produced. Consequently, our understanding of astronomical objects is frequently limited by a lack of accurate atomic data.

In this UROP project, laboratory emission spectra of singly ionised nickel will be analysed to measure electronic transition wavelengths which will then be used to optimise previously known, and discover new, atomic energy levels. Nickel is part of the important iron-group of elements which combine high relative abundances with rich spectra, making them extremely important in stellar spectroscopy. The results of this project will be added to atomic line databases, and from there, used internationally in stellar atmospheric models.  These are used to understand stellar and galactic evolution.

Skills and experience required: This project requires attention to detail and a through, careful approach to data analysis. An interest in astrophysics and python programming experience are pluses.

This UROP is offered on a remote basis, with the preferred length being 8 weeks full-time during the summer vacation. If on-campus attendance is possible this will be considered dependent on the College rules in force at the time, but it will not be essential.

A bursary is available to the successful applicant. The value of the bursary is £325 per week. Further details from the contact below

Contact details: Dr Christian Clear, Dept of Physics, Faculty of Natural Sciences, Huxley Building, Room H711A, South Kensington Campus. Email: christian.clear@imperial.ac.uk

 

NEW (10 June 2021)

Machine learning for predicting Wildfire duration and burned areas: Wildfire forecasting has received increasing attention in fire safety science world-widely. Firefighting resources allocation or evacuation of at-risk areas has much to benefit from numerical models which predicts the spread of the fire in space and time. The UROP participant will contribute to the project of applying machine/deep learning algorithms (e.g., random forest, CNN) to predict wildfire durations/burned areas based on satellite images and local environmental features. This project is in in the context of a collaboration between the Leverhulme Centre for Wildfires, Environment and Society and the Data Science Institute (DSI) at Imperial College London. The participant will be co-supervised by Dr.Sibo Cheng and Dr. Rossella Arcucci.

Skills and experience required: Python programming (experience with machine learning packages (e.g. sk-learn, Keras) is a plus), notions about machine learning algorithms.

 

This UROP is offered on a remote basis, with the preferred length being 8 weeks during the summer vacation. If on-campus attendance is possible this will be considered dependent on the College rules in force at the time, but it will not be essential.

A bursary is available to the successful applicant. The value of the bursary is £325 per week. Further details from the contact below.

Applications are especially welcomed by Black students, as well as from individuals who are members of current and historically underrepresented groups.

Contact details: Dr Sibo Cheng, Leverhulme Centre for Wildfires, Environment and Society, Department of Life Sciences, Imperial College London, South Kensington, London,SW7 2AZ. Email: sibo.cheng@imperial.ac.uk. Tel: +447485578412

NEW (10 June 2021)

Fire related vegetation properties in Amazon: Severe fire frequency affects vegetation biodiversity and structural properties. Amazon store large amount of carbon in vegetation and soils. Recent on-the-ground sample plots suggest high vulnerability of different forest types to fire in the southern Amazon-Cerrado transition including seasonal evergreen forest of Mato Grosso (Prestes et al., 2020) and tropical savanna of Columbia (Armenteras et al., 2021). Sensitivity of multispectral Landsat derived vegetation indices (VIs) to burned areas detection, fire severity and vegetation structural properties are extensively reported for tropics, temperate and boreal forest, however the potential of those VIs to fire related forest biophysical properties for tropical evergreen and savanna ecosystem are limitedly studied.

This project will investigate the potential of mapping fire related species diversity and structural properties using Landsat derived ten VIs across 5 sites of Amazon (2 sites in Mato Grosso, Pucallpa, Bojonawi Reserve, Columbian Upland). These sites have different fire regimes based on different vegetation types (seasonal forest, gallery forest, savanna woodland) with different fire frequency in different years. The output will be useful in understanding how wildfires affect vegetation properties at landscape level, developing fire regime definition for the tropics in the LCWES and present results in RSPSoc 2021 Conference.

Skills and experience required: Remote Sensing, Ecology, Analysis skills. Initiative as part of a team

The participant will be co-supervised by Dr Ramesh Ningthoujam and Prof. Colin Prentice

This UROP is offered on a remote basis, with the preferred length being 8 weeks during the summer vacation. If on-campus attendance is possible this will be considered dependent on the College rules in force at the time, but it will not be essential.

A bursary is available to the successful applicant. The value of the bursary is £325 per week. Further details from the contact below.


Applications are especially welcomed by Black students, as well as from individuals who are members of current and historically underrepresented groups.

Contact details: Dr Ramesh Ningthoujam, Leverhulme Centre for Wildfires, Environment and Society, Department of Life Sciences South Kensington, London, SW7 2AZ. Email: rningtho@ic.ac.uk.

Further readings:

  • Armenteras, D., Meza, M.C., González, T.M., Oliveras, I., Balch, J.K. and Retana, J. (2021). Fire threatens the diversity and structure of tropical gallery forests. Ecosphere, 12(1). e03347.
  • Prestes N.C.C.dos S., et al., including Feldpausch T.R., (2020). Fire Effects on Understory Forest Regeneration in Southern Amazonia, Frontiers in Forests and Global Change, 3, 1-10.
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