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Research Assistant / Research Associate (Data Scientist)

Job description

Research Assistant/Associate
Full time, fixed term for 24 months
£32,380 – £44,220 plus benefits
Reference ENG00219
Closing date 3 September 2018

Job Summary

We have an exciting opportunity for a Research Assistant/Associate to work on a joint initiative at Imperial College between the Data Science Institute (DSI), the Imperial NIHR Brain Sciences Theme - Division of Brain Sciences and the Institute for Translational Medicine and Therapeutics (ITMAT) Data Science Group to develop a Big Data translational platform for data curation, quality control and standardized analysis of complex imaging and phenotypic data.

Intended initially to rapidly enable more efficient exploitation of the UK Biobank ( dataset hosted at Imperial College, the platform is intended also to support emerging real-time, anonymized hospital administrative, laboratory and imaging data for research in the longer term. The initial focus will be on diseases of the brain, particularly including late-life dementias.

Duties and responsibilties

The successful candidate will be expected to exploit and contribute to the integration of high-throughput imaging data analysis methods, and to deploy advanced statistical analyses or machine-learning methods to discover associations between imaging features relevant to pathology and phenotypic data.

The post holder will work closely with expert collaborators and clinicians to understand their needs and research questions.

To apply you should have a track record of medical image computing with solid knowledge in handling/processing large and complex datasets; ability to conduct and complete research and development projects; working knowledge of specialized toolkits and libraries (e.g. in R, Matlab, Python) and generic coding languages (e.g. Java, Perl, C/C++); basic shell scripting in UNIX. Previous experience with SQL is a plus.

Essential requirements

  • To apply as a Research Associate you must have a PhD (or equivalent) in computer science, engineering, informatics or biomedical and/or biostatistics discipline with specific experiences in medical image computing or computer vision, machine learning, large-scale data analysis.
  •  At  Research Assistant level a good first degree (or equivalent) or Masters (or equivalent) in a related area, with a particular interest on medical image computing and machine learning. 
  •  A proven research record with publications in the relevant areas is also required
  •  Experience in medical image computing, such brain, cardiac or abdominal image analysis etc. Experience in brain image analysis will be preferred.
  •  Experience in handling/processing large datasets in batch mode
  • Experience in basic statistics, data mining and machine learning
  • You must have excellent verbal and written communication skills.

 *Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £32,380 to £34,040 per annum.

 Further information

Informal inquiries about the post can be directed to Dr Elsa Angelini .

 Closing date 03 September 2018


Research Associate

Full time, fixed term  position until 26 February 2020
Salary in the range: £37,904to £43,198 per annum plus benefits
Reference ENG00164
Location South Kensington Campus
Closing date: 13th September 2018

Job summary

The Data Science Institute (DSI), headed by Professor Yike Guo, is seeking an exceptional data analyst/data engineer to join an enthusiastic team to develop medical image data ware house and analysis platform. The DSI launched in April 2014 as Imperial College’s fifth cross-faculty Institute provides a focal point for multidisciplinary data-driven research, supplying technology support for partners, and educating the next generation of data scientists.

The postdoctoral researcher will work on the EPSRC funded smart heart project to develop the medical images management and analysis platform for cardiology research

Duties and responsibilities

You will be expected to fully collaborate with team members and collaborating with partner biomedical research projects on data management and analysis; providing training/support to technical and non-technical end-users; contributing to the dissemination of work within the group and also externally at national and international conferences by presentation, publication and demonstration. 

The successful candidate will be expected to: exploit and contribute to the development of the MRI scanning data warehouse based on the XNAT platform; to Integrate XNAT system with tranSMART system to provide clinician a unified platform for clinical study; develop automatic pipeline for data migration and integration; and to develop an intuitive web based interface to enable clinicians who may have little IT background to visualise population-level medical images and corresponding analysis results (such as segmentation results or phenotype statistics) and to retrieve cases of clinical interests.

Essential requirements

To apply you must have a PhD (or equivalent) in biomedical engineering,computer science or electrical engineering, and significant software development experience with an emphasis on image data management and analysis.

You should have a track record of data management, medical imaging, biomedical signal processing, algorithms and system design.  You must also have experience  of clinical medical images  and cardiology.

A proven research record with publications in the relevant areas is also required.  You must be fluent in English. 

Further information

Job description of SmartHeart

How to apply:
Via our website at  and search using vacancy reference number ENG00164
For queries regarding the application process contact Fay Miller
For technical issues when applying online, please contact:

Closing date:  13 September 2018

Research Associate/Assistant in Computational Privacy

Department of Computing, Data Science Institute
Research Associate/Assistant: Computational Privacy

Salary in the range:
Research Associate
£36,800 to £44,220 per annum

Research Assistant
Salary in the range: £32,380-£34,040

Fixed Term full time position until 10/05/2019
Closing date: 29th August 2018

Job Summary

The Computational Privacy Group , directed by Yves-Alexandre de Montjoye , at Imperial's Data Science Institute and Department of Computing has a funded opening for a Postdoc to work on computational privacy.  The group is interested in the original application of computational techniques such as machine learning and statistical physics on large behavioural datasets in order to identify privacy risks. The proximity with key industrial and institutional actors allows the group to explore unique and complex datasets leading to exciting and impactful research. The group’s research has been published in top tier journals such as Science and PNAS

Ever more individuals and companies have the ability to routinely amass massive amounts of data about individuals and the societies in which they live. Data generated by our technologies has the potential to fundamentally transform the way we fight diseases, design transportation systems, develop new drugs, etc. Improperly used, this data can also lead to deep violations of our privacy and large-scale discrimination. The goal of our work is to develop research and technical solutions allowing data to be used for good in a privacy-conscientious and fair manner.

Duties and Responsibilities

The research project will be defined in close collaboration with the successful candidate in the area of computational privacy. For example, possible projects could include the development of a rigorous framework to efficiently profile individuals based on behavioural data. The CPG’s research projects usually include a mix of theoretical and empirical work. The group also strives for active and constructive collaboration and the candidate will be expected to participate in the group’s research and may be expected to help supervise doctoral students.

Essential requirements

  • Candidates are expected to have (or be about to obtain in the near future) a PhD in applied mathematics, computer science, statistics, machine learning or a related quantitative field
  • A strong track-record of publications in leading journals or conferences.
  • Experience working with large datasets is required.
  • A demonstrated interest in the impact of privacy research on society (e.g. personal blog) is a plus.

Further information

How to apply:
Via our website at and search using vacancy reference number ENG00441.  In addition to completing the online application, candidates should attach:

A full CV

A 1 page statement indicating why your expertise is relevant

For queries regarding the application process contact Fay Miller

For technical issues when applying online, please contact: