PhD Studentship: Deep Learning in Mass Spectrometry Imaging (038117)

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).

These large and complex data require the use of data mining algorithms to identify features in the data. 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. Current techniques limit the volume of data that can be analysed, and currently there are no methods to integrate the different modalities produced by the instrument.  The 3D OrbiSIMS is the first of its kind and is involved in a large number of projects relating to antimicrobial resistance, cancer research, and material characterisation. The project offers a unique opportunity for candidates to contribute to a wide range of disciplines and impact a broad scientific base.

The work will concentrate upon machine learning, data-mining, statistical and pattern recognition techniques. The successful candidate will have knowledge and experience in machine and deep-learning, mathematics and computer science, prior knowledge of mass spectrometry imaging is desirable but not essential.

Department of Computer Science

The Department of Computer Scienceat the University of Surrey, within the Faculty of Engineering and Physical Sciences, has an international reputation for research and teaching. In the National Student Survey of 2015/16, overall student satisfaction was 95%. Research in the department is focused on two main areas: Nature Inspired Computing and Engineering (led by Prof. Jin), and Secure Systems.

National Physical Laboratory (NPL)

The National Physical Laboratory(NPL) is the national measurement standards laboratory for the United Kingdom with a long history of high quality research and excellent science. NPL has experimental capabilities in a wide range of scientific disciplines, including the National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI) which includes the 3D OrbiSIMS instrument. NPL also have expertise in machine learning and data science (Dr Thomas and Dr Chretien).

Responsibilities

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. The candidate will spent 50% of their time at Surrey and 50% at NPL working closely with experimental researchers acquiring the data. Successful applicants will attend conference and workshop to present their research, and also present regularly to wider research groups at both sites.

Qualifications

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 an understanding of a wide range of data analysis algorithms and tools and strong programming skills in languages such as C++, Java, Matlab, Python, etc. In addition, you must have good communication skills and be fluent in English. We look for a candidate that is self-motivated, engaging, and is a team player.

Studentship Funding

The Studentship consists of a fee waiver and a stipend of£14,553 ~ £18,553 per annum depending on experience and performance, and is available to students of UK/EU residency. This PhD student position is limited to four years.

The 4 year studentship will start from 1 October 2017, though can be delayed for the ideal candidate.

As a PhD student at University of Surrey, you have many opportunities to participate at conferences, projects and other relevant events which will extend your professional network and benefit your future career. Successful candidates will be expected to provide support in the Department’s course portfolio by helping out in lab sessions.

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 pageby clicking on the ‘apply online’ button.

In addition to the above, as part of your application, you are also required to upload the following documents:

- Statement of purpose (1-3 pages) where you introduce yourself, explain why do you want to pursue a PhD, present your qualifications and describe your future research plans;

- Research proposal describing your research area of interest and motivation. Are there any specific projects and research issues you are primarily interested in? Previous research fields and main research results should also be mentioned. It is important to include parts of your own work such as theses and articles that you have authored or co-authored. 

The application deadline is 30 June, 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 yaochu.jin@surrey.ac.uk or Dr. Spencer Thomas spencer.thomas@npl.co.uk

Closing Date: 30 Jun 2017
Category: PhD Studentships