PhD Studentship: Deep Learning in Mass Spectrometry Imaging

Updated: about 1 month ago
Location: Guildford, ENGLAND
Deadline: 14 Aug 2017

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Department of Computer Science
Location:  Guildford
Post Type:  Full Time
Advert Placed:  Friday 14 July 2017
Closing Date:  Monday 14 August 2017
Reference:  054717


Prof. Yaochu Jin (Surrey), Dr Spencer Thomas (NPL), Dr Stephane Chretien (NPL)

Funding amount

Fee waiver and a stipend of £14,553 ~ £18,553 per annum for a 4 year studentship

Funding source

EPSRC and NPL (3D nanoSIMS project)

(Note: This position is available to students who have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship)

Position Summary

Applications are invited for a cutting-edge fully funded Ph.D. project in deep learning hosted jointly at the Department of Computer Science, University of Surrey, UK and the National Centre of Excellent in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, UK. The new 3DOrbiSIMS instrument at NPL is the only one in the world and can produce large volumes of high dimensional multi-modal data in multiple dimensions (three spatial and one spectral). 

The research project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument in a time and memory efficient manner. The work will concentrate upon machine learning, data-mining, statistical and pattern recognition techniques. 

Responsibilities and Qualifications

The candidate will develop novel algorithms for mining, analysis, integration and validation of multimodal data generated from the 3DOrbiSIMS instrument. These will include the development of machine learning algorithms for mass spectrometry imagining data and the study of the fundamentals of deep learning using a large volumes of data produced at NPL. Successful applicants will attend conference and workshop to present their research, and also present regularly to wider research groups at both sites. 

Applicants will have a first class honours degree, or an upper second class honours degree in Computer Science, Mathematics, Physics, or related discipline. Candidates with other backgrounds and an appropriate MSc may also be considered. It is not mandatory to have the experience of working with mass spectrometry imaging data but this can be advantageous. The applicant should have strong programming skills in languages such as C++, Java, Matlab, Python, etc. You must have good communication skills, be fluent in English and self-motivated.

Application Procedure

The application process requires the submission of a CV, two letters of recommendation or contact information of two referees, attested copies of degree certificates and transcripts from all university-level courses taken. More information about how to apply can be found in the Computer Science PhD page by clicking on the ‘apply online’ button.

The application deadline is 14 August, 2017. Shortlisted applicants will be contacted directly to arrange a suitable time for an interview.

For any questions regarding the application process or an informal discussion about the position, please contact Prof. Yaochu Jin or Dr. Spencer Thomas 

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