Scholarships and funding
A list of funding opportunities for PhD applicants in the Information School.
There are a number of scholarship competitions you can enter to gain funding to study a PhD in the Information School for entry in October 2024.
Contact the School through the email ispgr@sheffield.ac.uk as soon as possible if you are thinking of applying, as the application process is complicated and we are able to support you.
There are a number of different schemes listed below. These are all highly competitive and you will need to tailor your application to the criteria for that particular scheme. Depending on your topic, however, you may be able to apply to more than one scheme. Before you apply, please check the award details and eligibility criteria for the scheme.
Most scholarships cover tuition fees and provide a stipend (student living allowance), plus a Research Training Support Grant to cover research costs and consumables. However, you should check the details of each scholarship when you apply.
The Information School departmental deadline (15 December 2023) for all scholarship applications has now passed.
1. ESRC White Rose DTP (WRDTP)
https://www.sheffield.ac.uk/postgraduate/phd/scholarships/esrc
These are for studies in the Social Sciences linked to pathway themes for the WRDTP, several of which are relevant to the Information School, but particularly “Data, Communication and New Technologies (DCT)”.
2. AHRC White Rose College of the Arts & Humanities (WRoCAH) Awards
https://wrocah.ac.uk/funding/prospective-students/
These are in the Arts and Humanities, including library and information studies (which falls under the WROCAH Creative Arts and Media cluster).
3. Chinese scholarship council
https://www.sheffield.ac.uk/postgraduate/phd/scholarships/csc
4. University of Sheffield
https://www.sheffield.ac.uk/postgraduate/phd/scholarships/faculty
The Faculties of Engineering, Health, and Social Sciences are accepting applications as part of an open University of Sheffield Research Scholarship competition for all applicants to their departments.
5. Information School GTA scholarships
The deadline for GTA Scholarships has now passed. Further details will be available once a new scholarship round is announced.
Project funding
In addition to these open scholarships, sometimes we have a specific project which already has funding attached. You need to demonstrate that you are better qualified to complete the project than other applicants.
You will not usually be asked to write a complete research proposal, but you may be asked to write a short personal statement, or provide a description of how you would approach the project.
Funded projects can be announced at any time of the year. You can sign up for alerts for these projects at jobs.ac.uk.
Currently available funded projects:
Interpretable Machine Learning Algorithms for Predictive Toxicology
Supervisor: Prof Val Gillet
Closes: 29th February 2024
EPSRC CASE Studentship. University of Sheffield and Syngenta Crop Protection
Machine learning is increasingly used for decision making and molecular design in the pharmaceutical and crop protection sectors to reduce the extensive time, costs and attrition associated with the development of new chemical entities. The typical aim is to relate molecular structure to predicted properties such as biological activity and toxicity. While complex machine learning algorithms such as Deep Learning and Random Forest have been shown to deliver good prediction performance, they yield so-called “black-box” models which are challenging to interpret. Recently various approaches have been reported for interpreting the predictions of “black-box” models with varying degrees of success. An alternative approach has been the development of “interpretable-by-design” methods which, although they may have reduced overall performance, are by their nature easier to interpret, hence provide greater confidence in a regulatory context and better support chemists optimising molecular structures. Interpretability is particularly important in crop protection when trying to design out potential issues with (eco-)toxicology, to avoid late-stage attrition.
The aims of this project are: the development of machine learning prediction methods that are both accurate and interpretable; and the extension of these methods to interspecies predictions to allow chemists to comprehend the reasons for species sensitivity.
This studentship opportunity is only open to home (i.e. UK) candidates.
Entry requirements are a minimum 2.1 undergraduate honours degree and/or MSc degree in a relevant science or engineering subject.
It will be an advantage if candidates have an interest in machine learning or artificial intelligence and computer programming skills. The student will spend a placement period working at Syngenta Crop Protection.
For more details on the entry requirements and research at the University of Sheffield, and how to apply, visit our department’s webpages at www.sheffield.ac.uk/is/phd
Funding
Fully funded 4 year studentship covering Home tuition fees, and an enhanced stipend for 4 years. The stipend pays the basic UKRI rate plus (currently £18,662 per annum for 23/24) plus an additional £4,000 per annum. There is also a generous research training and support grant to fund costs associated with the project.