PhD Studentship in the framework of the MSCA Doctoral Network GLITTER: Advanced Bayesian analysis and optimisation (Fixed Term)

University of Cambridge
May 18, 2024
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Fixed-term: The fund
Working Time:Full time
Working type:N/A
Ref info:N/A
PhD Studentship in the framework of the MSCA Doctoral Network GLITTER:

Advanced Bayesian analysis and optimisation (Fixed Term)

Fixed-term: The funds for this post are available for 36 months in the first instance.

Summary: Full-time PhD position funded by UKRI, in the context of the ERC doctoral network GLITTER (12 PhD students), to perform doctoral research in the development of modern antenna technology and radio instrumentation for GNSS-R and Radio Astronomy from space. The PhD candidate will join a multidisciplinary team and will be supervised by Dr Will Handley alongside data scientists at PolyChord Ltd (a spin-out company from the University of Cambridge) and researchers from Dr Will Handley's group based in the Kavli Institute for Cosmology, University of Cambridge. The PhD candidate will benefit from the GLITTER events in order to further improve technical and complementary skills: four one-week training schools, and three workshops. In addition, the PhD candidate will interact with CSIC and SYNTONY through 3 month secondments working with Dr Cardellach and Dr Carrie. `

Description: The next decade will see a revolution in satellite configuration and data processing, with the launch of large constellations of small satellites coincident with ever more demand for earth and sky monitoring. This PhD project aims to develop and apply the cutting edge of Bayesian analysis and machine learning to the optimisation of satellite configurations for GNSS-R. Combining the data science expertise of Dr Handley's Cambridge lab and PolyChord Ltd company with the expertise of the GLITTER network, the PhD candidate will build and deploy the next-generation of analysis tools for the future of satellite earth observation.

Projects will include:

  • Developing tools for optimising cubesat configurations using PolyChord algorithm as a global optimiser underarbitrary nonlinear constraints
  • Exploring the application of Bayesian parameter estimation, model comparison and tension quantification in GNSS-R problems
  • Applying the cutting edge of Likelihood-free inference techniques for simulation-based predictions
  • Exploring the use of machine learning emulators for enhancing the above processes in speed and accuracy
  • PolyChord Ltd is a spin-out company (SME) from the University of Cambridge, transferring technology from academia to industry, with current applications including rail monitoring, sensor placement optimisation, protein folding, and battery design. It has a long-term interest in the application of it's know- how and IP to the space sector, and the PhD candidate will be a key part of this process.

    Requirements for the candidate:

  • MSc degree in Physics, Engineering, Mathematics, Computer science or related fields.
  • Solid mathematical background, outstanding academic records, and excellent communication skills in oral and written English.
  • Strong Python programming & computing skills
  • Experience with Bayesian analysis, machine learning & high performance computing is desirable but not essential.
  • Application Process: The application process will be open until noon on 18th May. The applications received after this date will not be evaluated.

    Apply at the following email address: [email protected], the email must have a subject line starting with GLITTERAPPLICATION

    Please provide the following four items, all in pdf format:

  • Your CV (1 to 2 pages in pdf format)
  • A list of grades/diplomas, certificates
  • A list of referees (three at least)
  • A motivation letter
  • The four documents should be preferably assembled in a .zip file with a file name that starts with DC12.

    Questions regarding the recruitment can be sent to [email protected]. To be considered, the email must have a subject line starting with GLITTERQR

    Please quote reference KA41198 on your application and in any correspondence about this vacancy.

    The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

    The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


    Department of Physics, West Cambridge






    5 April 2024

    Closing date

    18 May 2024

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