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Education & Teaching Fellow (Data Science)

Imperial College London – Data Science Institute

Salary range: £44,510 - £53,800 per annum

Full time, fixed term appointment for 36 months

South Kensington Campus

An exciting opportunity has arisen to join our dynamic team at the Data Science Institute (DSI), Imperial College London as an Education and Teaching Fellow. This diverse role encompasses course development and support for the provision of data science education for students of various technical backgrounds and degree levels. In 2017/18 the DSI will be planning several new teaching initiatives with both industry and research partners, and this post holder will play an instrumental role in helping to design and teach these new programmes at PhD and executive level. The post holder will also be expected to design, deliver and support teaching to Imperial MSc and UG students, help plan and prepare further integration of data science education into existing College courses, and support the development of data science education.

It is anticipated that the DSI Education and Teaching Fellow will develop and deliver modules in data science for students on MSc and undergraduate courses within Imperial College Business School and the Faculty of Medicine in the first instance, as well as courses for postgraduate research students. The post holder will be expected to work alongside colleagues in the Institute to expand the provision of Institute’s education activities with other departments, and plan and implement the provision of summer schools and executive education programmes.

This is an exciting post for an energetic, passionate Data Science expert, allowing them to develop new and innovative ways to teach Data Science to students across multiple research backgrounds and platforms. The post holder must have a relevant first degree or a postgraduate qualification or equivalent in a relevant discipline. Additionally, applicants should have experience, or be able to demonstrate the potential to develop data science courses and to teach effectively and enthusiastically at university level. Data science technical competence is essential.

The DSI launched in April 2014 as Imperial College’s fifth cross-faculty Institute providing a focal point for multidisciplinary data-driven research, supplying technology support for partners, and educating the next generation of data scientists. It has grown quickly over the past two years, and continues to expand. Further information on the Data Science Institute can be found on our webpage.

Our preferred method of application is online via this website. Please download the following application form and save to your computer using the reference number EN20170154LE. Once completed, please upload your application form prior to submitting your application.

This post is equivalent to that of “Lecturer” in the United States. Informal e-mail enquiries may be made to Fay Miller at

Closing date: 21 June 2017

WorleyParsons PhD Studentship

The Data Science Institute (DSI) has a PhD studentship available.

Economics and society have gone digital, vast amounts of economic and social data are suddenly available. Understanding the impact data science has in the social and economic environment, such as the sharing economy, is crucial for the new era of Big Data.

In 2014 Imperial College London, established the Data Science Institute (DSI) which enhances Imperial's excellence in data-driven research across all its faculties.  The Data Economy Lab founded at the DSI brings together, Imperial College researchers and allied institutions, to discover how future economics will work in a Big Data context.

We are very pleased to provide a PhD studentship funded by WorleyParsons in the area of ‘Social and Economic Impacts of Data Science’, which starts in October 2017. The qualified candidate will work with our members in DSI to conduct high quality research in applying data-driven method in understanding and predicting economic impact on future societies, including new paradigm of data-driven economics, privacy protection in future data economy, and the role of Big Data in the sharing economy. 

The qualified candidate will team up with other researchers at Imperial (e.g. researchers from Imperial business school) to collaborate on interdisciplinary research topics.

Applicants should have knowledge in one or more of:

  • Machine learning
  • Data analysis and modelling
  • Economics/finance (especially data economy)
  • Mathematical finance, etc.

 A willingness to work independently and as part of a team on research is essential. In addition, the candidates should have (or be expecting to obtain) a first degree (1st class or upper second class) in computing, economics/finance or a relevant subject.

Eligibility and Funding:

The position is a full time position funded by Worley Parsons and the Data Science Institute covering tuition fees, travel funds and a stipend of £17K.

The position is available to UK/EU. If you are non-UK/EU national you can still apply, but you will need to make up the additional tuition fees for an overseas applicant.

Applicants should send by email to Prof Yi-Ke Guo ( their CV, details of academic qualifications and a short statement of your motivation and experience.

Deadline for application: until post filled

Start date: 01 October 2017

If you have any queries about the application process, please contact:

Dr. Amani El-Kholy at:

Or Fay Miller at:

PhD opportunity - Supporting human insight with AI in urban master plan design space exploration

Supporting human insight with AI in urban master plan design space exploration
 We have an exciting PhD opportunity with the Data Science Institute and Arup ( – a really really interesting company.  If you are interested, please get in touch.  If you know someone who might be interested please pass this email on to them.  Candidates will need a first-class MEng, MSci degree or distinction at MSc. 
Prof Paul Kelly (Software Performance Optimisation Group, Dept of Computing, Imperial College London,
Dr David Birch (Data Science Institute, Dept of Computing, Imperial College London,
This is a collaborative research project with Alvise Simondetti of Arup’s Foresight team (
Design is the process of balancing competing concerns – aesthetically and in performance across many objectives, e.g. reducing carbon emissions within a cost budget. Analysing design performance often relies upon computationally intensive analysis models (ray tracing for lighting, computational fluid dynamics for acoustics and pollution dispersal). Such expensive models make exploring the vast design space intractable and frequently only a couple of designs are quantitatively analysed. This means opportunities to shape a better world are missed.
The goal of this project is to develop novel tool support for tackling architectural design problems, focusing initially on urban masterplanning.  The key challenge is not outright automation or optimisation, but rather supporting humans in deriving insight, particularly to understand the most profitable and flexible parts of the design space.  We propose to extend our prior work with with Arup in this field with techniques from statistical machine learning, in particular the idea of Kriging (also known as Gaussian process regression) to derive a simplified “proxy” model that can be evaluated quickly.  Such models should help offer instant, interactive design feedback, as well as enabling us to identify the statistically most likely-profitable directions for further exploration, with respect to multiple design objectives.   
This project is funded under the EPSRC’s Industrial CASE scheme, which supports collaborative research which is based in the university but benefits from regular contact and guidance from our industry partner, Arup.
If you’re interested, please email Paul Kelly with your CV with a short covering email explaining why you think this might be for you – as soon as possible.

Research Assistant/Research Associate: OPTIMISE-MS

Research Assistant/Research Associate

Research Assistant salary in the range: £31,740 to £33,370 per annum
Research Associate salary in the range: £36,070 to £43,350 per annum

Fixed Term position up to 31st March 2018

We have an exciting opportunity for a Research Assistant/Associate to work at the Data Science Institute with the founding Director Professor Yike Guo and his team.

This is an exciting opportunity to join an enthusiastic team and a wider community of neuroscientists, clinicians, bioinformaticians, informaticians and research scientists to develop the precision medicine software infrastructure for the clinical multiple sclerosis management project OPTIMISE-MS. The project involves the integration of several open source data management tools – including the award-winning tranSMART data management platform and XNAT ( for medical images management – together into a platform for applications in multiple sclerosis research. This is one of the largest MS precision medicine projects in the country and has global impact. This is a great opportunity for someone interested in precision medicine and especially neuroinformatics to work with top clinical neurology groups from across the UK.  The researcher will work closely with partner clinicians to understand requirements of the informatics infrastructure.

At Research Assistant level you must have a good first degree (or equivalent) or Masters (or equivalent) in a related area.  At Research Associate level you must have a PhD (or equivalent) in computer science, engineering, informatics or biomedical and/or biostatistics discipline or significant experience.

You must have a proven track record of biomedical data management and analysis, experience in handling/processing large and complex datasets, solid knowledge of big data and data warehouse technology and a good knowledge of modern programming languages (Java, Python) and cloud computing management technology (e.g. Docker, openstack).  Experience working with SQL and UNIX/LINUX is also required. 

You will be based at the South Kensington campus. All applicants must be fluent in English.

How to apply:

Our preferred method of application is online: (please select “job search” then enter vacancy reference number EN20170124LE into “keywords”). 

 Please include:

    • A college application form
    • A full CV
    • A 1-page statement indicating what you see as interesting research issues relating to the above post and why your expertise is relevant.

For queries regarding the application process contact Georgina Tennant:

Closing Date: 30 May 2017

Imperial Managers lead by example.

Committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people

Research Associate (Data Assimilation)


Fixed Term appointment for 18 months to start as soon as possible

Salary in the range: £36,070 - £43,350 per annum*

The Data Science Institute (DSI) is seeking to recruit a Research Associate (Data Assimilation) to lead research into the development and application of advanced numerical techniques, in particular, reduced order modelling techniques. The Research Associate will work at the DSI with the Director Professor Yike Guo and his team. Within the DSI the post holder will be part of the Data Assimilation Lab.

The Data Science Institute (DSI) launched in April 2014 as Imperial College’s fifth cross-faculty Institute. The DSI provides a focal point for multidisciplinary data-driven research, supplying technology support for partners, and educating the next generation of data scientists.

The successful candidate will undertake internationally leading research into the development of a range of the next generation unstructured adaptive mesh air pollution/atmospheric and data assimilation models and applications to atmospheric modelling, air pollution and urban environmental problems. The Research Associate will collaborate with and strengthen the multi-disciplinary team of researchers already in place working on closely related projects. Ultimately the post holder will contribute to the delivery of a next generation unstructured mesh predictive model for optimising sensors, data assimilation and optimised controls. The work will contribute to the MAGIC project:

To apply you must have a PhD (or equivalent) in an area pertinent to the research subject e.g. Mathematics, Physics, Computing, Engineering. We are seeking candidates with a background in computational science, in particular optimisation, data analysis, and data assimilation techniques (adjoint, enKF etc), signal processing, in particular systems identification and filter theory and experience of implementation of data assimilation techniques within complex multi-physics unstructured adaptive mesh models, and in particular fluid dynamics. You must have excellent written communication skills and the ability to write clearly and concisely at a level consistent with publication in highly regarded international journals and be able to organise and prioritise your own workload with minimal supervision.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £31,740 - £33,370 per annum.

You will be based at the South Kensington campus. For information on the group see: All applicants must be fluent in English.

How to apply: Our preferred method of application is online via:  (please select “job search” then enter the job title or vacancy reference number EN20170145LE into “keywords”).

Please include:

* A college application form

* A full CV

* A 1-page statement indicating what you see as interesting research issues relating to the above post and why your expertise is relevant.

For queries regarding the application process contact Sarah Willis at:

Closing Date: 14 June 2017