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Centre for Doctoral Training in Data Intensive Science

The STFC Centre for Doctoral Training (CDT) in Data Intensive Science (DIS)

at UCL is welcoming applications from outstanding candidates for at least 10 4-year PhD studentships for research in DIS topics, predominantly in Astrophysics and Particle Physics, to start in the academic year 2019/20. The studentships comprise full UK/EU tuition fees and a tax-free maintenance allowance equivalent to that of standard STFC studentships (£16,777 pa in 2018/19). They also come with additional funding for travel and equipment. The deadline for applications is 25 January 2019.

The UCL CDT in DIS is the first Centre of its kind funded by STFC. UCL has a long-standing tradition of excellence in data intensive science, with pioneering contributions and leading roles in many international projects in Particle Physics and Astronomy, as well as a strong culture of cross-disciplinary research and collaboration between academia and industry. The Centre will build on these strengths to train the next generation of data science leaders and, together with its industrial partners, will accelerate the development and application of pioneering data intensive science techniques that promise to offer great benefits to the UK and global economy and to enrich the STFC science programme.

Centre for Doctoral Training in Data Intensive Science

About the Centre

Astrophysics, High Energy Physics and other Physical sciences are undergoing an ‘industrial revolution’ with huge data sets and complex models to describe them. For example, galaxy surveys, in which UCL is involved, will catalogue over the coming decade billions of galaxies. Similarly, Particle Physics experiments generate gigantic data sets.

The PhD studentships will be for four years. 'The CDT will prepare the next generation of scientists for both the data intensive challenges through dedicated training, a research project on a world-leading large-scale facility and a placements of six months in appropriate private, public or research organisations utilising data intensive techniques. We have already engaged over 25 industry partners in the programme. Our aspiration is that this will lead to academia-industry cross-fertilization and to breakthroughs in DIS methods and applications. DIS is a fast moving field, and we expect the courses to evolve accordingly in coming years.

Training and Research in the Centre

In their first year, students will benefit from a 150 hours of advanced training in data intensive science techniques, including a module on Machine Learning Techniques and an Industry Group Project, focussing on real-world DIS projects overseen by our Partners. This will be followed by the main thesis research project on a world-leading DIS experiment, with many students able to undertake a year-long placement at their experiment, for instance at CERN or Fermilab for the HEP stream.

Industry Placements

All students will undertake a 6-month placement project, entirely separate from their PhD project, at one of our 25 industry partners, which will provide them opportunity to learn about the tools, techniques, datasets and challenges present in industry. As well as furthering the student's training, it will also allow them to use their training to solve real-world problems and promote knowledge-transfer between academia and industry.

How to Apply

We will be looking for candidates with an outstanding academic record (first-class or upper-second class honours primarily in Physics but we also welcome applications from Engineering, Computer Science or closely related subjects at UK undergraduate Masters level or equivalent) coupled with a broad outlook and a strong interest in Data Intensive Science. We particular encourage applications from female students & students of ethnic minority backgrounds as these are currently underrepresented within the Physics industry.

Applicants should state in their application whether they are interested in a DIS research topic in Astrophysics, Particle Physics or another related DIS field. Inquiries can be addressed to the Centre’s PhD Admission Tutor, Prof. Serena Viti ([email protected]). The online application portal can be found at:

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