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February 2018 PhD Studentships

As part of our continuing recruitment process we invite further applications for four PhD studentships for projects in the field of Space Science, Space Instrumentation and Data Intensive Physics and Astronomy (see specific topics below). The expected start date is 1 February 2018.

The timetable for the recruitment process is outlined below:

  • Application deadline – 20  October 2017 (12.00pm midday)
  • Interview (at the Open University, Milton Keynes or Skype) – 15 November 2017

Please note: If you would like to apply then please send a completed application form, an up to date CV, list of individual courses taken and grades obtained, plus any other relevant information that you think may support your case for consideration, together with an indication of project(s) of interest to STEM-SPS-PhD-Admin by the application deadline. You are encouraged to contact the lead supervisor of the project(s) for any informal enquiries

Additional studentships in the School of Physical Sciences for starting in October 2018 will become available in the near future for a wide range of additional projects covering areas of Astronomy, Physics, Planetary and Space Sciences and Space Instrumentation.

Space Science and Space Instrumentation

Each of the following two projects has a dedicated studentship supporting it:

SS2: Investigation of microwave sintering as a potential fabrication method of Additive Manufacturing technologies for an extra-terrestrial construction processes.

Contact: Sungwoo Lim

SS3: Ion-molecule reactions and their implications on past, present and future space missions.

Contact: Andrew Morse

One studentship is also available to support one of the following projects:

SI1: Radiation damage in the Gaia focal plane: in-orbit data, charge-transfer simulations, and the impact on the astronomy achievable

Contact: David Hall

SI3: Development of an Imager for CubeSatellites

Contact: Professor Andrew Holland

SI4: Ultra-low noise CMOS image sensors

Contact: Dr Konstantin Stefanov

SI5: Novel techniques for probing radiation damage mechanisms and defect evolution in silicon devices

Contact: Dr Ben Dryer

SI6: Characterisation of the NOMAD detector on the ExoMars TGO mission
using machine learning

Contact: Manish Patel

Data Intensive Science

One studentship is also available to support one of the following data intensive projects in physics or astronomy:

DI - P1 Electron and positron scattering data for radiation bio-matter modelling

Contact: Jimena Gorfinkiel

DI - A1 Using machine learning to find gravitationally-lensed quasars and supernovae

Contact: Stephen Serjeant

DI - A2 Hunting for weirdos: a search for rare populations in multi-wavelength galaxy surveys using machine learning

Contact: Stephen Serjeant

DI - A3 The evolution of galaxy morphologies through deep learning
convolutional neural nets

Contact: Stephen Serjeant



Updated 20/09/2017